Difference between revisions of "Cs382"

From Earlham CS Department
Jump to navigation Jump to search
(Deleted "Activities in Manual" Section)
(Created Plume Tracking Section)
Line 87: Line 87:
 
*** - MYMPI is untested
 
*** - MYMPI is untested
 
**** Need to compile stuff.
 
**** Need to compile stuff.
 +
 +
=== Plume Tracking ===
 +
* Setup
 +
** physical simulator setup approximately 16 inches away and perpendicular to the line of sight of a web enabled camera.
 +
** A script was used to capture output of the output of the camera from the server at a rate of one every two seconds. A faster rate may be possible, but the current script did not have time to get the image and rename it within a 1 second interval.
 +
* Procedure
 +
** set pump flow rate at maximum and allow water table to equalize
 +
** start image capture script
 +
** inject a full pipette bulb into well number 1
 +
** remove pipette before allowing bulb to reinflate
 +
** allow simulator to run for approximately 5 minutes or until the majority of the dye in the system has been discharged
 +
** stop image capture script
 +
 +
We did three complete runs, each with a different dye colors.  We used blue, purple and green because we thought they would give the most contrast for edge detection.

Revision as of 22:00, 4 December 2007

This page documents the work of CS382 - Scientific Computing, Fall 2007


enVision Tabletop Groundwater Simulator

General Instructions

  • Setup
  • Teardown and cleaning
  • Packing and travelling

Instructions for Demonstrations

  • First one
  • Second one
  • etc.

Computational Groundwater Simulations

Fitz, Bryan and Mikio

Confined aquifier simulation
Parabolic contaminant flow model
  • Experiments
    • Demonstrating porosity
      • model water flow unconfined aquifier
    • Illustrating groundwater flow in a confined aquifer
      • We will use a cellular automata model where at the lowest level, a cell is either fresh water or contaminated. We see this problem split into two concepts - speed and direction.
        • Direction: The illustration to the right demonstrates our assumptions about how the water will move through the material. The simulation will calculate a new direction at each generation based on it's position relative to the known locations of water input and output.
        • Speed: Remains constant throughout generations for a given run. The "speed" value represents a combination of speed of water flow and material porosity, and in terms of the simulation is the possibility that a a neighboring cell in the flow direction becomes contaminated.
    • Describing recharge, transition and discharge areas
      • modeling behavior of water recharge, discharge in wells, lake, etc
  • Computational Tools
    • C
      • +Very fast
      • +Libraries are available
      • +Good distributed Libraries
      • -Potentially difficult to use
      • -no graphics libraries
    • Netlogo
      • +Fancy Graphics
      • +Fun to use
      • +Available examples/code
      • -Slow
      • -Small problem size
      • -No Distributed processing

Peter and Mikio

  • Experiment
    • Describing the model
      • Describing the various parts of the Groundwater Simulator by attaching tags: Key words -- wells, artesian wells, lake, underground storage tank, septic tank, springs, vegetative layer, river/ocean, recharge area, discharge area, aquifers, confining layer, clay layers
    • Illustrating and Calculating Porasity of different types of earth materials
    • Determining how it is easy for ground water to move in different earth materials.
  • Computetional Tool
    • NetLogo for computatinal experiment

Brad and Nate

Our goal is an incremental approach towards illustrating groundwater contamination in a confined aquifer. The confined aquifer, viewed between wells 1 and 8, offers an environment within the groundwater simulator with the fewest variables. The first 4 experiments are an effort to illustrate the behavior and underlying science that must be understood and demonstrated in the final experiment.

  • Experiments
    • Diffusion
      • Show diffusion without groundwater movement.
    • Flow Rate
      • Show the leading edge of groundwater contamination as a indicator of flow rate (related to section 5 and 13 in manual)
    • Contaminant Plume Length
      • Determine whether contaminant plume length is affected by flow rate for a given amount of dye
    • Soil Density
      • Use displacement method and measurements of aquifer component to determine the density of the soil. We can use this value in silico.
    • Illustrate laminar flow in a confined aquifer (Activity 7-1)
      • Show laminar flow between wells 1 and 8.
  • Computational Tools
    • NetLogo
      • + Visualization built in
      • + Agent and cell based simulation structure built in
      • - Possible limitation on world size / agent count in RAM
      • - Possible run time slower than groundwater simulator at higher flow rates
      • - Not parallel
    • Python and MYMPI
      • + Parallelizable
      • + Faster than NetLogo in serial code ?
      • + Visualization software exists
        • TKInter - easy to install; seemingly easy to use
      • - Visualization software must be integrated
      • - MYMPI is untested
        • Need to compile stuff.

Plume Tracking

  • Setup
    • physical simulator setup approximately 16 inches away and perpendicular to the line of sight of a web enabled camera.
    • A script was used to capture output of the output of the camera from the server at a rate of one every two seconds. A faster rate may be possible, but the current script did not have time to get the image and rename it within a 1 second interval.
  • Procedure
    • set pump flow rate at maximum and allow water table to equalize
    • start image capture script
    • inject a full pipette bulb into well number 1
    • remove pipette before allowing bulb to reinflate
    • allow simulator to run for approximately 5 minutes or until the majority of the dye in the system has been discharged
    • stop image capture script

We did three complete runs, each with a different dye colors. We used blue, purple and green because we thought they would give the most contrast for edge detection.