README

For information on how to get dfnWorks up and running, please see the document dfnWorks.pdf, in this directory. Documentation is also available here

https://lanl.github.io/dfnWorks/intro.html

Native build from github repository

This document contains instructions for setting up dfnWorks natively on your machine. To setup dfnWorks using Docker instead, see the next section.

Clone the dnfWorks repository

$ git clone git@github.com:lanl/dfnWorks.git

Set the LagriT, PETSC, PFLOTRAN, Python, and FEHM paths

Before executing dfnWorks, the following paths must be set:

• dfnWorks_PATH: the dfnWorks repository folder

• PETSC_DIR and PETSC_ARCH: PETSC environmental variables

• PFLOTRAN_EXE: Path to PFLOTRAN executable

• LAGRIT_EXE: Path to LaGriT executable

• FEHM_EXE: Path to FEHM executable

  $ vi dfnWorks/pydfnworks/pydfnworks/general/paths.py

For example:

os.environ['dfnWorks_PATH'] = '/home/<username>/dfnWorks/'    

Alternatively, you can create a .dfnworksrc file in your home directory with the following format

{
    "dfnworks_PATH": "<your-home-directory>/src/dfnWorks/",
    "PETSC_DIR": "<your-home-directory>/src/petsc",
    "PETSC_ARCH": "arch-darwin-c-debug",
    "PFLOTRAN_EXE": "<your-home-directory>/src/pflotran/src/pflotran/pflotran",
    "LAGRIT_EXE": "<your-home-directory>/bin/lagrit",
    "FEHM_EXE": "<your-home-directory>//src/xfehm_v3.3.1"
}

Note that you need to set the dfnworks_path, but the others are optional if you don't want to run those executables

Installing pydfnworks

Go up into the pydfnworks sub-directory:

$ cd dfnWorks/pydfnworks/

Compile The pydfnWorks Package & Install on Your Local Machine:

$ pip install -r requirements.txt

or

$ pip install -r requirements.txt --user

if you don't have admin privileges.

Note that the python version needs to be consistent with the current release

Installation Requirements for Native Build

Tools that you will need to run the dfnWorks work flow are described in this section. VisIt and ParaView, which enable visualization of desired quantities on the DFNs, are optional, but at least one of them is highly recommended for visualization. CMake is also optional but allows faster IO processing using C++.

Operating Systems

dfnWorks currently runs on Macs and Unix machine running Ubuntu.

Python

pydfnworks uses Python 3. We recommend using the Anaconda 3 distribution of Python, available at https://www.continuum.io/. pydfnworks requires the following python modules: numpy, h5py, scipy, matplotlib, multiprocessing, argparse, shutil, os, sys, networkx, subprocess, glob, mplstereonet, fpdf, and re.

LaGriT

The LaGriT meshing toolbox is used to create a high resolution computational mesh representation of the DFN in parallel. An algorithm for conforming Delaunay triangulation is implemented so that fracture intersections are coincident with triangle edges in the mesh and Voronoi control volumes are suitable for finite volume flow solvers such as FEHM and PFLOTRAN.

https://lagrit.lanl.gov

dfnWorks v2.8+ requires LaGriT v3.3. DFM meshing requires that LaGriT is built with exodus.

PFLOTRAN

PFLOTRAN is a massively parallel subsurface flow and reactive transport code. PFLOTRAN solves a system of partial differential equations for multiphase, multicomponent and multi-scale reactive flow and transport in porous media. The code is designed to run on leadership-class supercomputers as well as workstations and laptops.

http://pflotran.org

FEHM

FEHM is a subsurface multiphase flow code developed at Los Alamos National Laboratory.

https://fehm.lanl.gov

Paraview

Paraview_ is a parallel, open-source visualisation software. PFLOTRAN can output in .xmf and .vtk format. These can be imported in Paraview for visualization. While not required for running dfnWorks, Paraview is very helpful for visualizing dfnWorks simulations.

Instructions for downloading and installing Paraview_ can be found at http://www.paraview.org/download/