Welcome to PolyADCIRC’s documentation!

Python-based framework for running batches of parallel ADCIRC simulations with varying parameters (Manning’s n and limited variable bathymetry, etc). Includes documentation for a Python interface to a slightly modified verion of GridData (Griddata_v1.32.F90). GridData is a FORTRAN program originally developed by Seizo Tanaka (ST3) and C.H.Lab., University of Notre Dame.

This code also extends the PolyADCIRC framework to interface with a slightly modifed version of Subdomain ADCIRC v.50. Subdomain ADCIRC v.50 was developed by Alper Altuntas and Jason Simon under the direction of John Baugh; Department of Civil, Construction, and Enviromental Engineering North Carolina State University (NCSU), Raleigh, NC 27695.

All code documented here is written for Linux with a bash shell. It can be modified for other shells. This code requires GNU Parallel to be installed in order to run properly.

Note

If you plan on making ANY changes to the repos make a NEW branch!

Contents:

• Overview
  • Installation
  • Package Layout
  • Code Overview
  • Internal dependencies
  • External dependencies
• Running on Lonestar
  • File System Setup
  • Python Scripts
  • Job Submission Script
• Limited Variable Bathymetry
  • few_walls
  • load_few_walls
• Large Jobs
  • concatenation_2
  • concatenate_many
• All about mapping landuse data to the mesh
  • Preparing basis vector files from GAP/NLCD data
  • Comparing the Python vs. Griddata_v1.32.F90 Reconstructions
  • Manufacturing GAP data
• Running with Subdomain ADCIRC
  • Getting the Subdomain ADCIRC Code
  • Modifying Subdomain ADCIRC
  • Setting up the Subdomain grid_dir
  • Setting up your landuse_## folders
  • Running PolyADCIRC with Subdomains
• Some References and Examples
• polyadcirc
  • polyadcirc package
• Todo List

Todo

Add pictures and comment examples.

Indices and tables

• Index
• Module Index
• Search Page

Disclaimer

This code was originally developed for research purposes use at your own risk. Hopefully, the documentation is clear. You might find bugs I have overlooked. If you find something amiss please report this problem to me through GitHub or submit a fix. Thanks!

This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1110007. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.