Removing old docs and addressing build warnings. (#33)

doc/index.rst

@@ -18,11 +18,10 @@ multi-block and overset 3D CFD solver.
    introduction
    install
    tutorial
-   meshing
    options
    pyADflow
    solvers
    performance
    devguide
-   
+
 See Fortran code documentation `here <_static/doxydoc/html/index.html>`_

doc/tutorial.rst

@@ -3,24 +3,30 @@
 Tutorial
 ========
 
+Meshing
+-------
+
+Before running ADflow we need a CGNS mesh. For a complete tutorial on using MACH, including meshing, please refer to the `MACH aero tutorial <https://github.com/mdolab/MACH_Aero_Tutorials>`_.
+
+
 Basic Run Script
 ----------------
 
 The following shows how to get started with ADflow by running the mdo_tutorial
-wing problem. First, we show the complete program listing and then go through 
+wing problem. First, we show the complete program listing and then go through
 each statement line by line::
 
   # This is a template that should be used for setting up
   # RANS analysis scripts
-  
+
   # ======================================================================
   #         Import modules
   # ======================================================================
   import numpy
   from mpi4py import MPI
   from baseclasses import *
   from adflow import ADFLOW
-  
+
   # ======================================================================
   #         Input Information -- Modify accordingly!
   # ======================================================================
@@ -33,25 +39,25 @@ each statement line by line::
   MGCycle = '3w'
   altitude = 10000
   name = 'fc'
-  
+
   aeroOptions = {
   # Common Parameters
   'gridFile':gridFile,
   'outputDirectory':outputDirectory,
-  
+
   # Physics Parameters
   'equationType':'RANS',
-    
+
   # Common Parameters
   'CFL':1.5,
   'CFLCoarse':1.25,
-  'MGCycle':MGCycle, 
+  'MGCycle':MGCycle,
   'MGStartLevel':-1,
   'nCyclesCoarse':250,
   'nCycles':1000,
   'monitorvariables':['resrho','cl','cd'],
   'useNKSolver':False,
-    
+
   # Convergence Parameters
   'L2Convergence':1e-6,
   'L2ConvergenceCoarse':1e-2,
@@ -73,7 +79,7 @@ each statement line by line::
   # Print the evaluatd functions
   if MPI.COMM_WORLD.rank == 0:
       print funcs
-  
+
 
 Start by importing the ``adflow``, ``baseclasses``, and ``mpi4py``.::
 
@@ -101,31 +107,31 @@ a few flow conditions and reference values to be put into ``AeroProblem`` later.
   MGCycle = '3w'
   altitude = 10000
   name = 'fc'
-  
+
   aeroOptions = {
   # Common Parameters
   'gridFile':gridFile,
   'outputDirectory':outputDirectory,
-  
+
   # Physics Parameters
   'equationType':'RANS',
-    
+
   # Common Parameters
   'CFL':1.5,
   'CFLCoarse':1.25,
-  'MGCycle':MGCycle, 
+  'MGCycle':MGCycle,
   'MGStartLevel':-1,
   'nCyclesCoarse':250,
   'nCycles':1000,
   'monitorvariables':['resrho','cl','cd'],
   'useNKSolver':False,
-    
+
   # Convergence Parameters
   'L2Convergence':1e-6,
   'L2ConvergenceCoarse':1e-2,
   }
 
-Now, this is the actually solution part. We start by defining the ``AeroProblem``, 
+Now, this is the actually solution part. We start by defining the ``AeroProblem``,
 which is import from ``baseclasses``. We specify flow condtions and reference values
 into the ``aeroProblem``. We also tell the solver which solution values that
 we are interested in. In this case, we use the keyword ``evalFuncs``. ::
@@ -135,25 +141,25 @@ we are interested in. In this case, we use the keyword ``evalFuncs``. ::
   areaRef=areaRef, chordRef=chordRef,
   evalFuncs=['cl','cd'])
 
-Then, we create the ADflow instant. We also provide ADflow all the options that we 
+Then, we create the ADflow instant. We also provide ADflow all the options that we
 just specified above. ::
 
   # Create solver
   CFDSolver = ADFLOW(options=aeroOptions)
-  
+
 Now, we solve the CFD problem. ``CFDSolver(ap)`` is the command that actually
-solve the CFD. You can see print out from ADflow of each iteration here. This 
+solve the CFD. You can see print out from ADflow of each iteration here. This
 example will take just a couple minutes. ``CFDSolver.evalFunctions()`` return
 the function of interests we specified in ``AeroProblem``.::
 
   # Solve and evaluate functions
   funcs = {}
   CFDSolver(ap)
   CFDSolver.evalFunctions(ap, funcs)
-  
-Finally, we print out the value of `cd` and `cl`. We only print on the 
+
+Finally, we print out the value of `cd` and `cl`. We only print on the
 root processor. ::
- 
+
   # Print the evaluatd functions
   if MPI.COMM_WORLD.rank == 0:
   print funcs
@@ -181,12 +187,16 @@ Usually there is only one mode set at a time. When doing a rigid rotation beawar
 
 There are two common cases. The span of the wing is in, y direction (rotation about y-axis) or z direction (rotation about y-axis):
 
-NEED TO REFINE 
+NEED TO REFINE
 THIS DEPENDS ON THE COORDINATES
 1. Span is in y direction / rotation is about the y-axis. (rmode needs to be set to true)
-  * positive rotation (+deltaAlpha) will pitch the wing upwards 
+
+  * positive rotation (+deltaAlpha) will pitch the wing upwards
   * negative rotation (-deltaAlpha) will pitch the wing downwards
 
 2. Span is in z direction / rotation is about the z-axis (qmode needs to be set to true)
-  * negative rotation (-deltaAlpha) will pitch the wing upwards 
+
+  * negative rotation (-deltaAlpha) will pitch the wing upwards
   * positive rotation (+deltaAlpha) will pitch the wing downwards
+
+