This tutorial will apply OpenFOAM to simulate the flow effect on submerged object using the simpleFoam solver and the k-epsilon turbulence schema. The tutorial develops the case of a submarine model against a flow current; the velocity and pressure applied on the submarine will be analyzed on the model results and flow paths will be plotted to see the main patterns around the submarine. Model output visualization is performed on Paraview that allows the representation of velocity and pressure vectors over the submarine.

This tutorial will demonstrate the modelling configuration to simulate a power dissipator in an open channel. The dissipator design is proposed on the Stormwater Drainage Manual from the Drainage Services Department of Hong Kong and  OpenFOAM will be used for the simulation with the interFoam solver since two immiscible and isothermal fluids are involved (water and air). The main variable of interest on the dissipator simulation is flow velocity to assess the efficiency of the dissipator.

There are many Global Circulation Models (GCMs) with historic and future data of Precipitation, Maximum Temperature and Minimum Temperature for different emission scenarios. Data is available on daily timescale from particular servers, in this tutorial we will show the main characteristics of the NASA NCCS THREDDS Data Server that provide the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset that has two of the four greenhouse gas emissions scenarios. Data from this dataset is available from 1950 to 2100 separated on historic and future with a spatial resolution of 0.25 degrees (~25km x 25 km). The tutorial show the main parts of the web server and scripts in Python to locate the closest model cell and to recursively download group of records.

Evaluation of hydrological processes as evapotranspiration, runoff, routing and infiltration require data as precipitation, flow, temperature and radiation on a daily basis. Required data for the hydrological modeling need to be accurate and must be completed over the period of study. Many times historical data from hydrological stations are incomplete and present many gaps that can be filled by the use of Artificial Intelligence tools as the Keras library in Python.

This tutorial show the procedure to run a complete script for the filling of missing precipitation in one station by the use of data from 2 nearby stations. The Python script is done on a Jupyter Notebook.

Drinking and residual water treatment, water intake into hydroelectric power stations or water treatment for industrial processes require the removal of suspended particles by sedimentation tanks. These hydraulic structures have a slow speed water inlet and a geometry that allows the decantation or precipitation of sediments along the settler path.

OpenFOAM is a open source software for Computational Fluid Dynamics (CFD) modeling with a series of solvers for different flow conditions. In this case we have used the driftFluxFoam solver to represent sediment precipitation in a sedimentator in a transient simulation of 6400 seconds. The tutorial contains 2 videos with the model description and its simulation.

Evaluation of crop yield can be tedious because sampling methods requires the actual counting of fruits for a whole tree or canopy area. If we want to optimize this time demanding task we can use new and open source machine learning algorithms available. We have selected Scikit-Learn for this tutorial, a machine learning library in Python for it ease to use, the available documentation and the sort of available tools. 

The tutorial covers the whole procedure of image representation, point of interest selection, template matching, cluster analysis and fruit counting. Python scripting was done in Jupyter Notebook, it is interactive and allows the user to add more points of interest or remove inaccurate points.

For OpenFOAM modelers the representation of topography can be painful due to the unstabilities and complexities of the Bezier Surfaces in Salome Platform. It is more stable to create the mesh by importing a full textured surface on a format file compatible with Salome. This tutorial show the process to create a STL file from a GeoTiff(.tif) file by scripts in Python. We have used the OSGeo4W Shell that comes with the normal QGIS instalation because it comes with the gdal library already installed.