Minor typos

Author: fpalacios

_tutorials/design_features/Inviscid_2D_Unconstrained_NACA0012.md

@@ -1,5 +1,5 @@
 ---
-title: Unconstrained shape design of an transonic inviscid airfoil at a cte. AoA
+title: Unconstrained shape design of a transonic inviscid airfoil at a cte. AoA
 permalink: /tutorials/Inviscid_2D_Unconstrained_NACA0012/
 ---
 
@@ -39,7 +39,7 @@ The flow conditions of this numerical experiment are such that transonic shocks
 - Temperature = 273.15 K
 - Mach number = 0.8
 
-While more advanced design problems can be selected, such as those containing flow and/or geoemtric constraints, we will consider a simple unconstrained drag minimization problem here to get started. Please note that, becuase this is a 2D Euler problem without constratins, the expected minimmum drag is going to be zero (or a small value due to numerical error in the spatial integration of the equation). To achive that theoretical minimum will depend on the selected design variables and the hability of the optimizer to identify a global minimum.
+While more advanced design problems can be selected, such as those containing flow and/or geoemtric constraints, we will consider a simple unconstrained drag minimization problem here to get started. Please note that, because this is a 2D Euler problem without constraints, the expected minimum drag is going to be zero (or a small value due to numerical error in the spatial integration of the equation). To achieve that theoretical minimum will depend on the selected design variables and the ability of the optimizer to identify a global minimum.
 
 ### Mesh Description
 
@@ -160,20 +160,9 @@ Note that there are many other types of design variables available in SU2, and e
 ![NACA 0012 Pressure](../../Inviscid_2D_Unconstrained_NACA0012/images/naca0012_pressure_opt.png)
 Figure (3): Pressure contours for the baseline NACA 0012 airfoil.
 
-### Running SU2_GEO
-
-To prepare the ground for a future optimization with geometrical constratints it is interesting to execute the SU2_GEO software by typing 
-```
-$ SU2_GEO inv_NACA0012
-```
-The screen output of this software provides useful geometrical information (airfoil thickness, choord, etc) that the designer can use in the future, for example, by adding a basic geometrical constraint in the config file
-```
-OPT_CONSTRAINT= (AIRFOIL_THICKNESS > 0.12)
-```
-
 ### Running SU2
 
-The continuous adjoint methodology for obtaining surface sensitivities is implemented for several equation sets within SU2. After solving the direct flow problem, the adjoint problem is also solved which offers an efficient approach for calculating the gradient of an objective function with respect to a large set of design variables. This leads directly to a gradient-based optimization framework. With each design iteration, the direct and adjoint solutions are used to compute the objective function and gradient, and the optimizer drives the shape changes with this information in order to minimize the objective. Two other SU2 tools are used to compute the gradient from the adjoint solution (SU2_DOT) and deform the computational mesh (SU2_DEF) during the process. Note that if a geometrical constratint is added, its value and gradient will be coumpued by SU2_GEO
+The continuous adjoint methodology for obtaining surface sensitivities is implemented for several equation sets within SU2. After solving the direct flow problem, the adjoint problem is also solved which offers an efficient approach for calculating the gradient of an objective function with respect to a large set of design variables. This leads directly to a gradient-based optimization framework. With each design iteration, the direct and adjoint solutions are used to compute the objective function and gradient, and the optimizer drives the shape changes with this information in order to minimize the objective. Two other SU2 tools are used to compute the gradient from the adjoint solution (SU2_DOT) and deform the computational mesh (SU2_DEF) during the process. Note that if a geometrical constrains is added, its value and gradient will be computed by SU2_GEO
 
 ![NACA 0012 Adjoint](../../Inviscid_2D_Unconstrained_NACA0012/images/naca0012_psi_density.png)
 Figure (4): Adjoint density contours on the baseline NACA 0012 airfoil.

_tutorials/design_features/Inviscid_3D_Constrained_ONERAM6.md

@@ -27,14 +27,14 @@ The following tutorial will walk you through the steps required when performing
 
 ### Problem Setup
 
-The goal of this wing design problem is to minimize the coefficient of drag by changing the shape while imposing lift and wing section thickness constraints. As design variables, we will use a free-form deformation approach. In this approach, a lattice of control points making up a bounding box are placed around the geometry, and the movement of these control points smoothly deforms the surface shape of the geometry inside. We begin with a 3D fixed-wing geometry (initially the ONERA M6) at transonic speed in air (inviscid). The flow conditions are the same as for the previous [Inviscid ONERA M6](https://su2code.github.io/Tutorials/docs/Inviscid_OneraM6/) tutorial.
+The goal of this wing design problem is to minimize the coefficient of drag by changing the shape while imposing lift and wing section thickness constraints. As design variables, we will use a free-form deformation approach. In this approach, a lattice of control points making up a bounding box are placed around the geometry, and the movement of these control points smoothly deforms the surface shape of the geometry inside. We begin with a 3D fixed-wing geometry (initially the ONERA M6) at transonic speed in air (inviscid). The flow conditions are the same as for the previous ONERA M6 tutorial.
 
 ![Opt. ONERA Grid](../../Inviscid_3D_Constrained_ONERAM6/images/onera_grid.png)
 Figure (1): View of the initial surface computational mesh.
 
 ### Mesh Description
 
-The mesh consists of a far-field boundary divided in three surfaces (XNORMAL_FACES, ZNORMAL_FACES, YNORMAL_FACES), an Euler wall (flow tangency) divided into three surfaces (UPPER_SIDE, LOWER_SIDE, TIP), and a symmetry plane (SYMMETRY_FACE). The baseline mesh is the same as for the previous [Inviscid ONERA M6](https://su2code.github.io/Tutorials/docs/Inviscid_OneraM6/) tutorial. The surface mesh can be seen in Figure (1).
+The mesh consists of a far-field boundary divided in three surfaces (XNORMAL_FACES, ZNORMAL_FACES, YNORMAL_FACES), an Euler wall (flow tangency) divided into three surfaces (UPPER_SIDE, LOWER_SIDE, TIP), and a symmetry plane (SYMMETRY_FACE). The baseline mesh is the same as for the previous ONERA M6 tutorial. The surface mesh can be seen in Figure (1).
 
 ![Opt. ONERA FFD](../../Inviscid_3D_Constrained_ONERAM6/images/onera_ffd.png)
 Figure (2): View of the initial FFD box around the ONERA M6 wing, including the control points (spheres).

_tutorials/design_features/Turbulent_2D_Constrained_RAE2822.md

@@ -21,7 +21,7 @@ You can find the resources for this tutorial in the folder [Turbulent_Shape_Desi
 
 ## Tutorial
 
-The following tutorial will walk you through the steps required when performing shape design for the transonic turbulent airfoil using SU2 and the automatic differentiation tool. It is assumed that you have already obtained and compiled SU2_CFD, SU2_CFD_AD, SU2_DOT, SU2_DOT_AD, SU2_GEO, and SU2_DEF. The design loop is driven by the shape_optimization.py script, and thus Python along with the NumPy and SciPy Python modules are required for this tutorial. If you have yet to complete these requirements, please see the [Download](https://github.com/su2code/SU2/wiki/Download) and [Installation](https://github.com/su2code/SU2/wiki/Installation) pages. And do not forget to install the AD design capability [AD Build](https://github.com/su2code/SU2/wiki/AD-Build).
+The following tutorial will walk you through the steps required when performing shape design for the transonic turbulent airfoil using SU2 and the automatic differentiation tool. It is assumed that you have already obtained and compiled SU2_CFD, SU2_CFD_AD, SU2_DOT, SU2_DOT_AD, SU2_GEO, and SU2_DEF. The design loop is driven by the shape_optimization.py script, and thus Python along with the NumPy and SciPy Python modules are required for this tutorial. If you have yet to complete these requirements, please see the [Download](/docs/Download/) and [Installation](/docs/Installation/) pages. And do not forget to install the AD design capability [AD Build](/docs/AD-Build/).
 
 ### Background