TAMOC - Texas A&M Oilspill Calculator
TAMOC is a Python package with Fortran extension modules that provides various functionality for simulating a subsea oil spill. This includes methods to compute equations of state of gas and oil, dissolution, transport of single bubbles and/or droplets, and simulations of blowout plumes, including the development of subsurface intrusions, and estimation of initial bubble/droplet size distributions from source flow conditions.
For typical usage, please see the ./bin directory of the source distribution for various example scripts.
- Version 1.2.1: Corrected minor errors in translating between NetCDF objects
- and Numpy arrays to avoid a masked-array error and updated the dbm_phys.f95 function for the mass transfer rate by Kumar and Hartland so that the Reynolds number is defined before it is used.
- Version 1.2.0: Added biodegradation to the fate processes considered in the
- discrete bubble model (DBM).
- Version 1.1.1: Updated the ambient module interpolation method to be
- compatible with newer versions of numpy, updated a few of the ./bin examples to only read data provided with TAMOC, and updated all test cases to be compatible with slight changes in the dbm module that were done in Version 1.1.0.
- Version 1.1.0: Updated various modules to be compatible with Anaconda
- Python, including Scipy version 0.17.0 and higher. Fixed a couple bugs in the test cases where output files are not created correctly. Updated the documentation with some missing new variables.
- Version 1.0.0: Finalized the validation cases and tested the model for
- release. This is the first non-beta version of the model, and is the version for which journal publications have been prepared. Most of the changes going forward are expected to be new capabilities and improvements in the user interface: the model solutions are not expected to change appreciably.
Beta versions of the model:
- Version 0.1.17: Updated the modeling suite so that all of the save/load
- functions are consistent with the present model variables and attributes. Modified the bent plume model so that ambient currents can come from any direction (three- dimensional). Added a new test file for the bent plume model. Changed the convergence criteria for the stratified plume model.
- Version 0.1.16: Updated the bent plume model so that post processing is
- fully consistent with the simulation results. Also, added the capability for the bent plume model to stop at the neutral buoyancy level in the intrusion for a stratified case. Updated the equilibrium calculations in the dbm module so that it does not crash when the first few elements of the mixture disappear (go to zero) and to speed up the calculation when successive substitution indicates the mixture may be single phase, but is slowly converging: stability analysis is initiated early, which greatly improves performance for difficult cases.
- Version 0.1.15: Moved the particle tracking in the bent plume model inside
- the main integration loop, which then removes tp and sp from the model attributes and includes then in the model state space instead. Updated the bent plume model state space so that particle mass is the state variables instead of particle mass flux and so that the dissovled phase constituents are modeled as total mass in the Lagrangian element instead of concentration times mass of the element. Made a small update to the hydrate formation time equations.
- Version 0.1.14: Updated several aspects of the calibration after comparing
- to available data in Milgram (1983), Jirka (2004), Socolofsky and Adams (2002, 2003, 2005), Socolofs et al. (2008), and Socolofsky et al. (2013). The most significant change is an updated shear entrainment coefficient for the stratified plume model. Also, added a buoyant force reduction as bubbles drift away from the centerline in a crossflow.
- Version 0.1.13: Updated the temperature output for the bent plume model so
- that the correct temperature is saved when heat transfer ends.
Added the particle time to the state space of the stratified
plume model and added the hydrate formation model of Jun et
al. (2015) to the particle objects in the dispersed phases
module. The hydrate formation time is set at the start of a
simulation and is properly implemented for all three
simulation modules in the
TAMOCsuite. To compute the hydrate formation time using the equations from Jun et al. (2015), use the function dispersed_phases.hydrate_formation_time.
- Version 0.1.12: Replaced methods for equilibrium and viscosity with better
- algorithms. Fixed small inconsistencies in the dbm.py module for clean bubbles, and updated the seawater equations of state with better methods for heat capacity and air/water surface tension. Updated values for the Setschenow constant in ./data/ChemData.csv, and added a mass transfer equation for Re < 1.
- Version 0.1.11: Replaced some of the -9999 values in the ./data/ChemData.csv
- file with literature values and updated the units of the calcualtion of Vb in dbm.py when data are not available. Also, updated the parameter values for the stratified plume model with the values recommended in Socolofsky et al. (2008).
- Version 0.1.10: Updated the values for Vb in the ./data/ChemData.csv file
- with their correct values. Improves computation of diffusivity and mass transfer over Version 0.1.9, and gives results similar to Version 0.1.8 and older that used a different method to estimate diffusivity.
- Version 0.1.9 : Made several minor changes to the equations of state per the
- guidance of Jonas Gros. These changes make the model much more robust for hydrocarbon mixtures. The updates are minor in that the results do not change markedly for the test cases already in previous versions of the model. However, the changes provide major advantages for more difficult cases, not demonstrated in the simple ./bin examples.
- Version 0.1.8 : Added print capability to the params.py module and upgraded
- the shear entrainment model in the bent_plume_model.py to the entrainment equations in Jirka 2004.
- Version 0.1.7 : Added the capability for the bent_plume_model.py to continue
- to track particles outside the plume using the single_bubble_model.py. Fixed a bug where particles outside the plume continued to dissolve and add mass to the bent_plume_model.
- Version 0.1.6 : Added a new simulation module for plumes in crossflow: the
- bent_plume_model.py. Refactored some of the code for the original model suite to make it more general and to reuse it in the bent_plume_model. Added example files and unit tests for the new modules, and updated the documentation to reflect all model changes.
- Version 0.1.5 : Fixed a small bug in the way the bubble force is handled
- after the particle dissolves. Fixed a bug to retain mass conservation for a bubble size distribution using the sintef.rosin_rammler() function.
- Version 0.1.4 : Added script for the the sintef and params modules to the
- ./bin examples directory and the /test unit tests. Improved the stability of the model by added a few new checks during and before calculation. Updated the unit tests to make them more platform and numpy-version independent.
- Version 0.1.3 : Removed some of the debugging catches in the iteration so that
- solutions always fully converge and fixed a few bugs. See CHANGES.txt for full details. Added the sintef.py module for computing initial bubble/droplet size distributions.
- Version 0.1.2 : Refined the test suite for compatibility with multiple
- versions of numpy and scipy. Corrected a few more minor bugs.
- Version 0.1.1 : Full modeling suite with small bug fixes and complete test
- Version 0.1.0 : First full modeling suite release, including the stratified
- plume module.
- Version 0.0.3 : Updated to include the single bubble model and the ambient
- module for handling ambient CTD data. Includes input and output using netCDF files and a complete set of tests in ./tamoc/test
- Version 0.0.2 : First model release, including the discrete bubble model
Version 0.0.1 : Initial template of files using setup.py
This package requires:
- Python 2.3 or higher
- Numpy version 1.6.1 or higher
- Scipy version 0.17.0 or higher
- A modern Fortran compiler
- netCDF4: try: easy_install netCDF4
For interaction with ROMS output, TAMOC also requires:
- octant: download from https://github.com/hetland/octant
- mpl_toolkits.basemap: download from http://sourceforge.net/projects/matplotlib/files/matplotlib-toolkits/
Code development and testing for this package was conducted in the Mac OS X environment, Version 10.9. The installed Python environment was the Enthought Canopy Distribution 18.104.22.1681 for Python version 2.7.3 (64-bit).
Fortran files are written in modern Fortran style and are fully compatible with gfortran 4.6.2 20111019 (prerelease). They have been compiled and tested by the author using f2py Version 2.
- Edit setup.cfg to select the appropriate C/C++ and Fortran compilers
- Run 'python setup.py build' followed by 'python setup.py install' (with sudo if necessary).
- Test the installation by opening a Python session and executing import tamoc from the Python prompt. Be sure that you are not in the same directory as the setup.py file so that Python will look for tamoc in the main Python package repository on your system.
- To run all the tests, cd to the ./test directory and execute 'py.test' from a command prompt. If pytest is not installed, follow the instructions here: http://pytest.org/latest/getting-started.html
The following method has been tested for installation on Windows 7.
- Install a complete Python distribution that includes Python, Numpy, and Scipy with versions compatible with the above list. Testing has been completed by the author using a 32-bit Python installation. The Python distribution will have to be compatible with your C/C++ and Fortran compiler. The free compilers available from MinGW that work with Python f2py are typically 32 bit. There are work-arounds, but the instructions here were all tested on 32-bit installations.
- Download and install the MinGW compiler suite. During installation, be sure to select a C, C++, and Fortran compiler. See, http://sourceforge.net/projects/mingw/files/
- Edit the Windows > System > Environment Variables so that the PATH can find your Python and MinGW installation.
- Open a command prompt from Start > Run > Command Prompt and follow the steps in the Quick Start section above to complete installation.
Mac OS X / Unix
The following method has been tested for installation on Mac OS X 10.7.
- Install a complete Python distribution that includes Python, Numpy, and Scipy with versions compatible with the above list. Testing has been completed by the author using a 32-bit and 64 bit Python installations. The Python distribution will have to be compatible with your C/C++ and Fortran compiler.
- Install the free XCode app in order to provide C/C++ compiler capability. Be sure to install the command-line tools.
- Download and install the gfortran binary. See, http://gcc.gnu.org/wiki/GFortranBinaries
- Follow the steps in the Quick Start section above to complete installation.