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@@ -2,59 +2,80 @@
 PyDPF-Post
 ==========
 
-The Data Processing Framework (DPF) provides numerical simulation 
-users and engineers with a toolbox for accessing and transforming simulation 
-data. With DPF, you can perform complex preprocessing or postprocessing of
-large amounts of simulation data within a simulation workflow.
+The Data Processing Framework (DPF) is designed to provide numerical
+simulation users/engineers with a toolbox for accessing and
+transforming simulation data.
 
-DPF is an independent, physics-agnostic tool that you can plug into many 
-apps for both data input and data output, including visualization and 
-result plots. It can access data from solver result files and other neutral
-formats, such as CSV, HDF5, and VTK files.
+The Python `ansys-dpf-post` package provides a high level, physics oriented API for postprocessing.
+Loading a simulation (defined by its result files) allows you to extract simulation metadata as well
+as results and apply postprocessing operations on it.
 
-Using the many DPF operators that are available, you can manipulate and
-transform this data. You can also chain operators together to create simple
-or complex data-processing workflows that you can reuse for repeated or
-future evaluations.
-
-The data in DPF is defined based on physics-agnostic mathematical quantities 
-described in self-sufficient entities called *fields*. This allows DPF to be 
-a modular and easy-to-use tool with a large range of capabilities. 
-
-.. image:: images/dpf-flow.png
-  :width: 670
-  :alt: DPF flow
-
-The ``ansys.dpf.post`` package leverages the ``ansys.dpf.core`` package, which
-is available at `PyDPF-Core GitHub <https://github.com/pyansys/DPF-Core>`_. With
-PyDPF-Core, you can build more advanced and customized DPF workflows.
+This module leverages the PyDPF-Core project's ``ansys-dpf-core`` package and can
+be found by visiting [PyDPF-Core
+GitHub](https://github.com/pyansys/pydpf-core).  Use ``ansys-dpf-core`` for
+building more advanced and customized workflows using Ansys DPF.
 
 
 Brief demo
 ~~~~~~~~~~
-Here is how you open and plot a result file generated by Ansys Workbench or
-MAPDL:
+
+Provided you have ANSYS 2023 R1 installed, a DPF server will start
+automatically once you start using PyDPF-Post.
+Loading a simulation for a MAPDL result file to extract and post-process results:
 
 .. code:: python
 
     >>> from ansys.dpf import post
     >>> from ansys.dpf.post import examples
-    >>> solution = post.load_solution(examples.multishells_rst)
-    >>> stress = solution.stress()
-    >>> stress.xx.plot_contour(show_edges=False)
+    >>> simulation = post.load_simulation(examples.download_crankshaft())
+    >>> displacement = simulation.displacement()
+    >>> print(displacement)
+
+
+.. rst-class:: sphx-glr-script-out
+
+ .. code-block:: none
+
+             results         U
+              set_id         3
+      node      comp
+      4872         X -3.41e-05
+                   Y  1.54e-03
+                   Z -2.64e-06
+      9005         X -5.56e-05
+                   Y  1.44e-03
+                   Z  5.31e-06
+       ...
+
+.. code:: python
 
+    >>> displacement.plot()
 
-.. figure:: ./images/main_example.png
+
+.. figure:: ./images/crankshaft_disp.png
+    :width: 300pt
+
+.. code:: python
+
+    >>> stress_eqv = simulation.stress_eqv_von_mises_nodal()
+    >>> stress_eqv.plot()
+
+.. figure:: ./images/crankshaft_stress.png
     :width: 300pt
 
-    Basic stress contour plot
+To run PyDPF-Post with Ansys versions starting from 2021 R1 to 2022 R2, use the following legacy PyDPF-Post
+tools:
 
-Here is how you extract the raw data as a :class:`numpy.ndarray` array:
 .. code:: python
 
-   >>> stress.xx.get_data_at_field(0)
-   array([-3.37871094e+10, -4.42471752e+10, -4.13249463e+10, ...,
-           3.66408342e+10,  1.40736914e+11,  1.38633557e+11])
+    >>> from ansys.dpf import post
+    >>> from ansys.dpf.post import examples
+    >>> solution = post.load_solution(examples.download_crankshaft())
+    >>> stress = solution.stress()
+    >>> stress.eqv.plot_contour(show_edges=False)
+
+.. figure:: ./images/crankshaft_stress.png
+    :width: 300pt
 
 
 For comprehensive demos, see :ref:`gallery`.