PPT-Cellular Automaton Evacuation Model Coupled with a Spatial

Anton von Schantz Harri Ehtamo a ntonvonschantzaaltofi harriehtamoaaltofi The document can be stored and made available to the public on the open internet pages of Aalto University All other rights are reserved. COMP308. Unconventional models and paradigms. Failure and Success of . Complex Models. New . scientific paradigms bring about new insights:. Research shows that complexity is a prerequisite for success of living systems (Jacobs, Langton, Wolfram, Kaufmann, . Daria Karpenko. Department of Mathematics and Statistics, University of South Florida. Simulating Cellular Automata at Temperature 1. Outline. Introduction. Overview of DNA self-assembly. DNA nanotech, DNA computing, and Applications. Building an idealised coupled system. Polly Smith, Amos . Lawless, Alison Fowler*. School of Mathematical and Physical Sciences, University of Reading, UK. * funded by NERC. Outline. Recap. objectives. Michele . Rienecker. Global Modeling and Assimilation Office. NASA/GSFC. WMO CAS Workshop. Sub-seasonal to Seasonal Prediction. Met Office, Exeter. 1 to 3 December 2010 . 2. What do we mean by “coupled data assimilation”?. Suharsh Sivakumar. December 11, 2010. Cellular Automaton. A grid of cells where all the cells are governed by a common set of rules based on the number of adjacent neighbors.. As generations go by, the rules work together to show very interesting phenomena in the big picture. . isopycnic. grids. Rainer Bleck, Shan Sun, . Haiqin. Li, Stan Benjamin. NOAA Earth System Research Laboratory. Boulder, Colorado. April 2016. Design . goals. :. (some reached, some pending). Global domain. Hilya Arini. Tim Bedford, John Quigley, Calvin Burns. Background. Research Objectives. Research . Methods. Outline. If . the fire alarm in this room. . suddenly rings. ,. . w. hat . would. you do?. calls. CW2015. Kristian. S. . Mogensen. Marine Prediction . Section. k.mogensen@ecmwf.int. Overview of talk:. Baseline:. The focus of this talk is going to be on coupling of IFS and WAM to NEMO. Motivation. 1. Saha-UMAC-09Aug2016. Atmosphere. , Land, Ocean, . Seaice. , Wave, . Chemistry, . Ionosphere. Data Assimilation cycle. Analysis frequency H. ourly. Forecast length . 9 . hours. Resolution . 10 . Brandon Kerns*, . Shuyi. S. Chen, . Chiaying. Lee, and . Falko. . Judt. RSMAS/University of Miami. I. nterdepartmental . H. urricane . C. onference Miami, Florida 28 February – 3 March 2011 . Asynchronous I/O. Navy ESPC (global coupled model). COAMPS (regional coupled model). Radiative transfer model (experimental). [New] NEPTUNE (global atmosphere). [New] NAAPS/aerosol model. Space Science Division . Participationin COREs(Coordinated Ocean-ice Coupled OceanCoupled Ocean--Ice Models Ice Models within the CSM Frameworkwithin the CSM Framework -HYCOM PanAm2.1 (hybri-Normally 2-26 vertical layers-CI In 2003, the U.S. Department of Energy (DOE) set up seven regional partnerships across the North American Region to study the technologies and strategies of CO. 2. sequestration and CO. 2. enhanced oil recovery (EOR). . Cihan. Kaya. 12/15/2015. Aims. Build and simulate a spatial model of dopaminergic signaling.. Investigate the effects of . Spatial distribution or surface density fluctuations of dopamine transporters.