From f284ce5f72df514d9f88098c135044ed248b3b65 Mon Sep 17 00:00:00 2001 From: schmoelder Date: Mon, 26 Aug 2024 09:15:32 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20master=20from=20@=20cadet/CADE?= =?UTF-8?q?T-Website@34444dc9c07c97ff415ebaa770647139e53b86e3=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- CADET-Match/master/.buildinfo | 2 +- .../master/.doctrees/cli/examples.doctree | Bin 9435 -> 9435 bytes .../master/.doctrees/cli/index.doctree | Bin 11640 -> 11640 bytes .../configuration/basic_config.doctree | Bin 12372 -> 12372 bytes .../.doctrees/configuration/error.doctree | Bin 16419 -> 16419 bytes .../configuration/experiments.doctree | Bin 11625 -> 11625 bytes .../.doctrees/configuration/graphing.doctree | Bin 7220 -> 7220 bytes .../.doctrees/configuration/index.doctree | Bin 7299 -> 7299 bytes .../.doctrees/configuration/misc.doctree | Bin 11833 -> 11833 bytes 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0a7602756..0c0674765 100644 --- a/master/_sources/developer_guide/cadet_core_architecture.rst.txt +++ b/master/_sources/developer_guide/cadet_core_architecture.rst.txt @@ -1,4 +1,4 @@ -.. _cadet_core_architecture +.. _cadet_core_architecture: Software Architecture ===================== @@ -33,10 +33,9 @@ Implementation Details ^^^^^^^^^^^^^^^^^^^^^^ Classes and realationships -Include figure 3.4 and/or 3.6 from Sams Diss .. _LibcadetClasses: -.. figure:: architecture_libcadet_classes.png +.. figure:: _images/architecture_libcadet_classes.png Selected relationships of classes in ``libcadet`` [1]_. diff --git a/master/_sources/developer_guide/cadet_python.rst.txt b/master/_sources/developer_guide/cadet_python.rst.txt new file mode 100644 index 000000000..1da8c269b --- /dev/null +++ b/master/_sources/developer_guide/cadet_python.rst.txt @@ -0,0 +1,273 @@ +.. _cadet_python: + +CADET-Python Introduction +========================= + +The CADET-Python API can be very useful for developers as it allows to create an arbitrary input configuration for CADET-Core. +This is especially useful when new methods and models are added, which are not (yet) supported by the CADET-Process frontend. +To demonstrate the use of CADET-Python, we set up a simulation in the following. + +Performing a forward simulation comprises several steps: + * Setting up the model including all parameters and discretization options + * Defining sections and switches + * Setting up the simulator and actually running the simulation + * Evaluating results (e.g., plotting) + +In this tutorial, we will build a simple forward simulation with a breakthrough of one component using the following system: + +.. figure:: _images/breakthrough_system.png + +For this purpose, we use :ref:`CADET-Python `, a file based frontend for CADET. +CADET still must be downloaded (or built from source) as explained in the :ref:`installation guide `. +The Python frontend almost exactly maps to the documented :ref:`CADET file format ` except that all dataset names are lowercase. +This simplifies using the frontend. +The package includes a ``Cadet`` class which serves as a generic HDF5 frontend. + +As an example, we consider setting the external porosity for the column model (``unit_001``). +From :ref:`file format `, the path for this is ``/input/model/unit_001/COL_POROSITY``. +In the Python frontend, this becomes: + +.. code-block:: Python3 + + sim = Cadet() + sim.root.input.model.unit_001.col_porosity = 0.33 + +0. Preliminary Steps +-------------------- + +First, we need to import some libraries and specify the location of the ``cadet-cli`` executable (core simulator). +It is located in the ``bin`` folder where CADET was installed. + +.. literalinclude:: examples/breakthrough.py + :lines: 2-6 + + +To create the model and specify its parameters, we create an instance of the ``Cadet`` class. +In the ``root`` attribute of this object, the parameter structure is defined as described in the :ref:`file format reference `. +It is implemented as a ``Dict`` of the |addict package|_. +This allows for creating arbitrary nested dictionaries using dot-notation. + +.. |addict package| replace:: ``addict`` package +.. _addict package: https://github.com/mewwts/addict + +.. warning:: Note, that the ``Cadet`` class does not provide any sanity checks. + If parameters are misspelled or have the wrong dimensions, they are simply ignored. + This can cause problems later on, when the simulator is run. + +.. literalinclude:: examples/breakthrough.py + :lines: 9 + + +1. Setting Up the Model +----------------------- + +Although the order of the parameter specification does not matter, it is reasonable to first specify the number of unit operations before we select the models and define the parameters. + +.. literalinclude:: examples/breakthrough.py + :lines: 12 + +The available models are listed in the :ref:`unit operation chapter `. +The units of the different parameters and quantities are given in the corresponding :ref:`file format ` of the respective unit operation. + +Inlet Model +^^^^^^^^^^^ + +In CADET, the ``INLET`` pseudo unit operation serves as a source for the system and is used to create arbitary concentration profiles as boundary conditions. +First, we define an ``INLET`` as the first unit operation by adding the field ``unit_000`` in the ``/input/model/`` group. +The concentration profile is described using a piecewise cubic polynomial (cubic spline in the continuous case) for each component, where the pieces are given by the time sections. +Later, we will define the polynomials, when we look at time sections. + +.. literalinclude:: examples/breakthrough.py + :lines: 15-17 + +General Rate Model +^^^^^^^^^^^^^^^^^^ + +We now add a second unit operation, the column model. +For the :ref:`general rate model model `, we set the ``unit_type`` parameter of the corresponding unit operation model to ``GENERAL_RATE_MODEL``. +In this group, we set the parameters related to transport and column geometry. +For a more detailed description of the parameters and their units, see the :ref:`corresponding file format `. + +.. literalinclude:: examples/breakthrough.py + :lines: 20-34 + +Note that film, particle, and surface diffusion are all component-specific, that is, they are vectors of length ``n_components``. + +Adsorption Model +~~~~~~~~~~~~~~~~ + +Every column model can be equipped with an adsorption model. +The available models are listed in the :ref:`binding model chapter `. + +For the :ref:`Langmuir model `, we set the ``adsorption_model`` parameter of the corresponding unit operation model to ``MULTI_COMPONENT_LANGMUIR``. +Then, we decide if we want to use the :ref:`rapid-equilibrium assumption ` in the binding model (``is_kinetic = False``), which is not the case here (dynamic binding). +Finally, the parameters of the binding model have to be set for each component (they are vectors of length ``n_components``). +They are described in the :ref:`corresponding file format specification `. +In case of the Langmuir model, we have to specify the parameters ``kA``, ``kD``, and ``qMAX``. + +.. literalinclude:: examples/breakthrough.py + :lines: 37-41 + +Initial Conditions +~~~~~~~~~~~~~~~~~~ + +Next, we specify the initial conditions (concentration of the components in the mobile and stationary phases) for the column. +These concentrations are entered as vectors, where each entry gives the concentration for the corresponding component. +In this example, we start with an empty column. + +.. literalinclude:: examples/breakthrough.py + :lines: 44-45 + +Setting up the Discretization +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +There are several options for adapting the spatial discretization of the PDE model. +However, the two most important ones are the number of grid cells in the column (axial direction) and the particles, which are also set in this example. +We choose ``20`` axial cells in the column ``ncol`` and ``5`` radial cells in the particle ``npar``. + +.. warning:: These are rather low values to make the examples run faster, since they are only for educational purposes. + In practice, much higher values are expected (say 100-200 axial cells and 16-32 particle cells). + Note that the WENO scheme, which handles the advection, drastically reduces the required amount of cells compared to an upwind scheme. + +Moreover, we have to specify the number of bound states for each component. +Finally, we set some other options for the discretization, which usually do not need to be changed. + +.. literalinclude:: examples/breakthrough.py + :lines: 48-66 + +Outlet Model +^^^^^^^^^^^^ + +The ``OUTLET`` is another pseudo unit operation that serves as sink for the system. + +.. note:: In this case, the outlet unit is actually not required. We could use the outlet concentration signal of the column model instead. + +.. literalinclude:: examples/breakthrough.py + :lines: 69-70 + + +2. Setting up Time Sections and Connections +------------------------------------------- + +Time Sections +^^^^^^^^^^^^^ + +:ref:`Time sections ` are used to specify changes of parameter values during the simulation. +A section typically corresponds to an operating step (load, wash, elute etc.), but can also be used to indicate changes in connectivity, or even discontinuities of :ref:`model parameters `. + +In the ``/input/solver/sections/`` group, ``nsec`` denotes the number of sections. +The start and end times of a section are given in the ``section_times`` vector. +It should always start at ``0.0`` and contains ``nsec + 1`` values, that is, the ``i``\ th section goes from ``section_times[i]`` to ``section_times[i+1]``. + +The ``section_continuity`` indicates whether a transition from one section to the next is continuous in both the inlet and the parameters. +It has ``nsec - 1`` number of values, since there is one transition less than there are sections. +The continuity is used in CADET’s time integrator, which needs to decide whether to restart on entering a new section. +If the transition is continuous, the time integrator can try to step over the transition without restarting, thus saving some computation time (since the restart is costly). +If you are unsure about the continuity, just leave it at ``0``. + +.. literalinclude:: examples/breakthrough.py + :lines: 73-75 + +As mentioned earlier, we now define the ``INLET`` profile using a piecewise cubic polynomial. +On each section :math:`[ t_i, t_{i+1} ]` a cubic polynomial :math:`p_i` is defined: + +.. math:: + + p_i( t ) = d * (t - t_i)^3 + c * (t - t_i)^2 + b * (t - t_i) + a, + +where the coefficients of the polynomial are ``const_coeff`` (a), ``lin_coeff`` (b), ``quad_coeff`` (c), and ``cube_coeff`` (d). +Note that the constant coefficient ``const_coeff`` determines the starting concentration on each section. +The stopping concentration is given by :math:`p_i( t_{i+1} )` or :math:`p_{i+1}( t_{i+1} )` in case of a continuous profile. + +In this example, which has only one section, we define its coefficients by adding the field ``sec_000`` to the inlet unit (``unit_000``). +Since the column should be constantly fed with :math:`1.0 \cdot 10^{-3} mol / m^3`, we set ``const_coeff`` to ``[1.0e-3]`` and all other cofficients to ``[0.0]``. +Note that for more components, a vector of coefficients needs to be specified. + +.. literalinclude:: examples/breakthrough.py + :lines: 78-81 + +System Connectivity +^^^^^^^^^^^^^^^^^^^ + +In order to specify the :ref:`connectivity of the network `, we have to provide a list of connections. +CADET requires that we append all connections to a long vector (i.e., if each connection is a row in a matrix, CADET wants this matrix in row-major storage). +Moreover, we have to specify the section in which the specified connectivity should be applied. + +The elements of a connection are (in order): + + ``[UnitOpID from, UnitOpID to, Component from, Component to, Volumetric flow rate]`` + +Usually, ``Component from`` and ``Component to`` can be set to ``-1``, which will connect all components from the origin and destination unit operations. + +.. note:: Since CADET version 4.1, the flow rates can also be defined with piecewise cubic polynomials. + Also, for the 2D General rate model inlet ports need to be speciefied. + For more information on the parameters, see the :ref:`file format specification `. + +In this case, we connect all components of ``unit_000`` to ``unit_001``, and from ``unit_001`` to ``unit_002``. + +.. literalinclude:: examples/breakthrough.py + :lines: 84-88 + +.. note:: Since the flow in the column models is incompressible, the total entering flow rate must equal the total outgoing flow rate. + This restriction does not apply to a :ref:`CSTR model `, because it has a variable volume. + +3. Setting Up the Simulator and Running the Simulation +------------------------------------------------------ + +Before we can start the simulation, we have to specify some settings for the simulator. + +First, we set some options for the solver and the time integrator. +Usually, these only need to be adapted in special cases. + +.. literalinclude:: examples/breakthrough.py + :lines: 91-104 + +Of these options, the most interesting ones are ``time_integrator.abstol`` and ``time_integrator.reltol``, which control the errors during time integration, and ``nthreads``, which sets the number of CPU cores CADET is allowed to use. + +Second, we have to specify which results we want CADET to return. +For this, we have to specify the ``/input/return/`` group. +For more information, see the :ref:`file format specification `. + +.. note::Because ``return`` is a reserved keyword in Python, we cannot use dot-notation but have to use the ‘proper’ dictionary indexing syntax. + +In this example, we want to write the concentration profile of the inlet and outlet of each unit operation. +In addition, we are interested in the concentration in the interstitial volume (bulk volume) of the column. + +.. literalinclude:: examples/breakthrough.py + :lines: 106-115 + +Finally, we have to set the time points at which we want to evaluate the solution. +Note that the end time must not exceed the last section time specified in the model. +If the time points are not set explicitly, the time integrator outputs the solution at arbitrary time points between ``0`` and ``section_times[-1]``. + +.. literalinclude:: examples/breakthrough.py + :lines: 117-118 + +The last remaining step is to actually run the simulation. +For this, we have to specify a filename, save the configuration to ``H5``-format and call call the ``model``\ ’s ``run()`` function. +We check if the simulation has completed successfully and load the results. + +.. literalinclude:: examples/breakthrough.py + :lines: 121-131 + +4. Plotting the Results +----------------------- + +The data is stored in the ``/output/`` group of the ``Cadet`` object. +The structure and format of the data is described in the :ref:`file format specification `. +Finally, we plot the concentration signal at the outlet of the column. + +.. literalinclude:: examples/breakthrough.py + :lines: 134-141 + +.. image:: _images/breakthrough_chromatogram.png + + +Exercises +--------- + +- Add a second inlet section from ``10000`` to ``40000`` seconds in which no sample is fed into the column (rectangular pulse). +- Increase the length of the column and the flow rate. +- Increase the desorption coefficient ``MCL_KD``. +- Add a second component. +- Plot the concentration profile of the ``INLET`` unit operation diff --git a/master/_sources/developer_guide/debugging.rst.txt b/master/_sources/developer_guide/debugging.rst.txt index c5498c95f..be41856a8 100644 --- a/master/_sources/developer_guide/debugging.rst.txt +++ b/master/_sources/developer_guide/debugging.rst.txt @@ -1,4 +1,4 @@ -.. _debugging +.. _debugging: CADET-Core debugging ==================== diff --git a/master/_sources/developer_guide/index.rst.txt b/master/_sources/developer_guide/index.rst.txt index 17525f597..8afb1ff93 100644 --- a/master/_sources/developer_guide/index.rst.txt +++ b/master/_sources/developer_guide/index.rst.txt @@ -14,6 +14,9 @@ Since some developers may be new to collaborative software development using Git .. toctree:: + :maxdepth: 2 + + cadet_python cadet_core_architecture build_options model_expansion diff --git a/master/_sources/developer_guide/testing.rst.txt b/master/_sources/developer_guide/testing.rst.txt index 932046d1e..890a7b85d 100644 --- a/master/_sources/developer_guide/testing.rst.txt +++ b/master/_sources/developer_guide/testing.rst.txt @@ -1,4 +1,4 @@ -.. _testing +.. _testing: CADET-Core testing ================== diff --git a/master/_sources/getting_started/installation.rst.txt b/master/_sources/getting_started/installation.rst.txt index dc5170e12..3c05ffbb5 100644 --- a/master/_sources/getting_started/installation.rst.txt +++ b/master/_sources/getting_started/installation.rst.txt @@ -13,12 +13,10 @@ If you want to extend or modify CADET (e.g., add a custom binding model), you wi Install pre-built binaries ^^^^^^^^^^^^^^^^^^^^^^^^^^ -CADET can be installed via conda from the ``conda-forge channel``. +CADET can be installed via `conda `_ from the ``conda-forge channel``. ``conda install -c conda-forge cadet`` -This requires a working `conda installation `_. - Optionally, use `mamba `_ which uses a faster dependency solver than ``conda``. ``mamba install -c conda-forge cadet`` @@ -30,29 +28,29 @@ Install from source - :ref:`build_windows` - :ref:`build_osx` -.. _cadet_python: +.. _cadet_process: Install a frontend ------------------ -As of now, only a Python frontend is provided. +CADET provides a Python API, called ``CADET-Python``, which can be used to set the model input according to the Interface specifications section. +Setting up the model using ``CADET-Python`` can become very tedious, especially for systems, and is outdated now that an actual frontend is available: -Install CADET-Python -^^^^^^^^^^^^^^^^^^^^ +We recommend using the ``CADET-Process`` frontend, which facilitates modeling processes using an object oriented model builder. +This interface layer provides convenient access to all model parameters in the system. +It automatically checks validity of the parameter values and sets reasonable default values where possible. -The easiest way to create CADET simulations is to use the `CADET-Python `_ frontend. -For this purpose, we recommend installing `Anaconda `_. -Anaconda is a high-performance scientific distribution of Python that includes many common packages needed for scientific and engineering work. -Download the installer from their `website `_ and run it for the local user. +Install CADET-Process +^^^^^^^^^^^^^^^^^^^^ -To install ``CADET-Python``, open an `Anaconda Shell` and execute: +To install ``CADET-Process``, open an `anaconda shell` or `mamba shell` and execute: .. code-block:: bash - pip install cadet-python + pip install CADET-Process -If you would also like to use `CADET-Match `_ for parameter estimation, run: +If you want to use ``CADET-Python``, open an `anaconda shell` or `mamba shell` and execute: .. code-block:: bash - pip install cadetmatch + pip install CADET-Python \ No newline at end of file diff --git a/master/_sources/getting_started/overview.rst.txt b/master/_sources/getting_started/overview.rst.txt deleted file mode 100644 index 086e36ba8..000000000 --- a/master/_sources/getting_started/overview.rst.txt +++ /dev/null @@ -1,64 +0,0 @@ -.. _overview: - -CADET Overview -============== - -Performing a forward simulation comprises several steps: - -.. toctree:: - :maxdepth: 1 - -For this example, we will use CADET-Python (see :ref:`cadet_python`) -CADET-Python is a file based interface for CADET. -CADET still must be downloaded and built from https://github.com/modsim/CADET - -CADET-Python almost exactly maps to the documented CADET interface except that all dataset names are lowercase. -This simplifies using the interface. - -This package includes the Cadet class and H5 class. -H5 can be used as a simple generic HDF5 interface. - -As an example look at setting column porosity for column 1. -From the CADET manual the path for this is /input/model/unit_001/COL_POROSITY - -In the python interface this becomes -`` -sim = Cadet() sim.root.input.model.unit_001.col_porosity = 0.33 -`` -Once the simulation has been created it must be saved before it can be run -`` -sim.filename = "/path/to/where/you/want/the/file.hdf5" sim.save() -`` - -Define unit operation parameters --------------------------------- -See also: :ref:`unit_operation_models` - -Define adsorption and reaction paramters ----------------------------------------- -See also: :ref:`binding_models`, and :ref:`FFAdsorption` - -See also: :ref:`reaction_models`, and :ref:`FFReaction` - - -Setup connections and switches ------------------------------- -See also: :ref:`simulation`, and :ref:`networks`, - -See Tables :ref:`FFModelSystemConnections` and :ref:`FFModelConnectionSwitch`. - - -.. image:: sections.png - - -Configure solver ----------------- - - -Call solver and read results ----------------------------- - -`` -sim.load() -`` - diff --git a/master/_sources/getting_started/tutorials/breakthrough.rst.txt b/master/_sources/getting_started/tutorials/breakthrough.rst.txt index dc9447f54..f0cabaf76 100644 --- a/master/_sources/getting_started/tutorials/breakthrough.rst.txt +++ b/master/_sources/getting_started/tutorials/breakthrough.rst.txt @@ -2,134 +2,86 @@ CADET Introduction ================== Performing a forward simulation comprises several steps: - * Setting up the model including all parameters and discretization options - * Defining sections and switches + * Setting up the model including all parameters + * Defining connectivity and dynamic events * Setting up the simulator and actually running the simulation * Evaluating results (e.g., plotting) In this tutorial, we will build a simple forward simulation with a breakthrough of one component using the following system: -.. figure:: _images/breakthrough_system.png +.. figure:: _images/breakthrough_system.svg -For this purpose, we use :ref:`CADET-Python `, a file based frontend for CADET. -CADET still must be downloaded (or built from source) as explained in the :ref:`installation guide `. -The Python frontend almost exactly maps to the documented :ref:`CADET file format ` except that all dataset names are lowercase. -This simplifies using the frontend. -The package includes a ``Cadet`` class which serves as a generic HDF5 frontend. +For this purpose, we use `CADET-Process `_, an object oriented Python frontend for CADET. +CADET still must be downloaded (or built from source) as explained in the :ref:`installation guide `. -As an example, we consider setting the external porosity for the column model (``unit_001``). -From :ref:`file format `, the path for this is ``/input/model/unit_001/COL_POROSITY``. -In the Python frontend, this becomes: +.. figure:: _images/cadet_architecture_overview.png -.. code-block:: Python3 - - sim = Cadet() - sim.root.input.model.unit_001.col_porosity = 0.33 - -0. Preliminary Steps --------------------- - -First, we need to import some libraries and specify the location of the ``cadet-cli`` executable (core simulator). -It is located in the ``bin`` folder where CADET was installed. - -.. literalinclude:: ../../examples/breakthrough.py - :lines: 2-6 - - -To create the model and specify its parameters, we create an instance of the ``Cadet`` class. -In the ``root`` attribute of this object, the parameter structure is defined as described in the :ref:`file format reference `. -It is implemented as a ``Dict`` of the |addict package|_. -This allows for creating arbitrary nested dictionaries using dot-notation. - -.. |addict package| replace:: ``addict`` package -.. _addict package: https://github.com/mewwts/addict - -.. warning:: Note, that the ``Cadet`` class does not provide any sanity checks. - If parameters are misspelled or have the wrong dimensions, they are simply ignored. - This can cause problems later on, when the simulator is run. - -.. literalinclude:: ../../examples/breakthrough.py - :lines: 9 + Relations between CADET-Core, CADET-Python, and CADET-Process. +For more information on how to set up models using CADET-Python, a plain file based API for CADET, please refer to the :ref:`cadet_python`. 1. Setting Up the Model ----------------------- -Although the order of the parameter specification does not matter, it is reasonable to first specify the number of unit operations before we select the models and define the parameters. +We first create a ``ComponentSystem``. +The ``ComponentSystem`` ensures that all parts of the process have the same number of components. +Moreover, components can be named which automatically adds legends to the plot methods. .. literalinclude:: ../../examples/breakthrough.py - :lines: 12 + :lines: 2-5 -The available models are listed in the :ref:`unit operation chapter `. -The units of the different parameters and quantities are given in the corresponding :ref:`file format ` of the respective unit operation. Inlet Model ^^^^^^^^^^^ -In CADET, the ``INLET`` pseudo unit operation serves as a source for the system and is used to create arbitary concentration profiles as boundary conditions. -First, we define an ``INLET`` as the first unit operation by adding the field ``unit_000`` in the ``/input/model/`` group. +In CADET, the ``Inlet`` pseudo unit operation serves as a source for the system and is used to create arbitary concentration profiles as boundary conditions. The concentration profile is described using a piecewise cubic polynomial (cubic spline in the continuous case) for each component, where the pieces are given by the time sections. -Later, we will define the polynomials, when we look at time sections. - -.. literalinclude:: ../../examples/breakthrough.py - :lines: 15-17 - -General Rate Model -^^^^^^^^^^^^^^^^^^ - -We now add a second unit operation, the column model. -For the :ref:`general rate model model `, we set the ``unit_type`` parameter of the corresponding unit operation model to ``GENERAL_RATE_MODEL``. -In this group, we set the parameters related to transport and column geometry. -For a more detailed description of the parameters and their units, see the :ref:`corresponding file format `. +In this example we set a constant inlet concentration of 1 mM. .. literalinclude:: ../../examples/breakthrough.py - :lines: 20-34 + :lines: 9-13 -Note that film, particle, and surface diffusion are all component-specific, that is, they are vectors of length ``n_components``. +Column Model +^^^^^^^^^^^^ Adsorption Model ~~~~~~~~~~~~~~~~ -Every column model can be equipped with an adsorption model. +Every unit operation model can be equipped with an adsorption model. The available models are listed in the :ref:`binding model chapter `. -For the :ref:`Langmuir model `, we set the ``adsorption_model`` parameter of the corresponding unit operation model to ``MULTI_COMPONENT_LANGMUIR``. -Then, we decide if we want to use the :ref:`rapid-equilibrium assumption ` in the binding model (``is_kinetic = False``), which is not the case here (dynamic binding). +For the :ref:`Langmuir model `, we use the ``Langmuir`` class. +Then, we decide if we want to use the :ref:`rapid-equilibrium assumption ` in the binding model (``binding_model.is_kinetic = False``), which is not the case here (dynamic binding). Finally, the parameters of the binding model have to be set for each component (they are vectors of length ``n_components``). -They are described in the :ref:`corresponding file format specification `. -In case of the Langmuir model, we have to specify the parameters ``kA``, ``kD``, and ``qMAX``. +All model parameters can be listed using the ``parameters`` attribute. +In case of the Langmuir model, we have to specify the parameters ``adsorption_rate``, ``desorption_rate``, and ``capacity``. .. literalinclude:: ../../examples/breakthrough.py - :lines: 37-41 + :lines: 18-24 -Initial Conditions +General Rate Model ~~~~~~~~~~~~~~~~~~ -Next, we specify the initial conditions (concentration of the components in the mobile and stationary phases) for the column. -These concentrations are entered as vectors, where each entry gives the concentration for the corresponding component. -In this example, we start with an empty column. +We now add a second unit operation, the column model. +For the :ref:`general rate model model `, we use the ``GeneralRateModel`` class. +In this class, we set the parameters related to transport and column geometry. .. literalinclude:: ../../examples/breakthrough.py - :lines: 44-45 - -Setting up the Discretization -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + :lines: 28-42 -There are several options for adapting the spatial discretization of the PDE model. -However, the two most important ones are the number of grid cells in the column (axial direction) and the particles, which are also set in this example. -We choose ``20`` axial cells in the column ``ncol`` and ``5`` radial cells in the particle ``npar``. +Note that film, pore, and surface diffusion are all component-specific, that is, they are vectors of length ``n_components``. -.. warning:: These are rather low values to make the examples run faster, since they are only for educational purposes. - In practice, much higher values are expected (say 100-200 axial cells and 16-32 particle cells). - Note that the WENO scheme, which handles the advection, drastically reduces the required amount of cells compared to an upwind scheme. +Initial Conditions +~~~~~~~~~~~~~~~~~~ -Moreover, we have to specify the number of bound states for each component. -Finally, we set some other options for the discretization, which usually do not need to be changed. +Next, we specify the initial conditions (concentration of the components in the mobile and stationary phases) for the column. +These concentrations are entered as vectors, where each entry gives the concentration for the corresponding component. +In this example, we start with an empty column. .. literalinclude:: ../../examples/breakthrough.py - :lines: 48-66 + :lines: 45-47 + -Outlet Model ^^^^^^^^^^^^ The ``OUTLET`` is another pseudo unit operation that serves as sink for the system. @@ -137,131 +89,51 @@ The ``OUTLET`` is another pseudo unit operation that serves as sink for the syst .. note:: In this case, the outlet unit is actually not required. We could use the outlet concentration signal of the column model instead. .. literalinclude:: ../../examples/breakthrough.py - :lines: 69-70 - - -2. Setting up Time Sections and Connections -------------------------------------------- + :lines: 50-52 -Time Sections -^^^^^^^^^^^^^ - -:ref:`Time sections ` are used to specify changes of parameter values during the simulation. -A section typically corresponds to an operating step (load, wash, elute etc.), but can also be used to indicate changes in connectivity, or even discontinuities of :ref:`model parameters `. - -In the ``/input/solver/sections/`` group, ``nsec`` denotes the number of sections. -The start and end times of a section are given in the ``section_times`` vector. -It should always start at ``0.0`` and contains ``nsec + 1`` values, that is, the ``i``\ th section goes from ``section_times[i]`` to ``section_times[i+1]``. - -The ``section_continuity`` indicates whether a transition from one section to the next is continuous in both the inlet and the parameters. -It has ``nsec - 1`` number of values, since there is one transition less than there are sections. -The continuity is used in CADET’s time integrator, which needs to decide whether to restart on entering a new section. -If the transition is continuous, the time integrator can try to step over the transition without restarting, thus saving some computation time (since the restart is costly). -If you are unsure about the continuity, just leave it at ``0``. - -.. literalinclude:: ../../examples/breakthrough.py - :lines: 73-75 - -As mentioned earlier, we now define the ``INLET`` profile using a piecewise cubic polynomial. -On each section :math:`[ t_i, t_{i+1} ]` a cubic polynomial :math:`p_i` is defined: - -.. math:: - - p_i( t ) = d * (t - t_i)^3 + c * (t - t_i)^2 + b * (t - t_i) + a, - -where the coefficients of the polynomial are ``const_coeff`` (a), ``lin_coeff`` (b), ``quad_coeff`` (c), and ``cube_coeff`` (d). -Note that the constant coefficient ``const_coeff`` determines the starting concentration on each section. -The stopping concentration is given by :math:`p_i( t_{i+1} )` or :math:`p_{i+1}( t_{i+1} )` in case of a continuous profile. - -In this example, which has only one section, we define its coefficients by adding the field ``sec_000`` to the inlet unit (``unit_000``). -Since the column should be constantly fed with :math:`1.0 \cdot 10^{-3} mol / m^3`, we set ``const_coeff`` to ``[1.0e-3]`` and all other cofficients to ``[0.0]``. -Note that for more components, a vector of coefficients needs to be specified. - -.. literalinclude:: ../../examples/breakthrough.py - :lines: 78-81 System Connectivity ^^^^^^^^^^^^^^^^^^^ -In order to specify the :ref:`connectivity of the network `, we have to provide a list of connections. -CADET requires that we append all connections to a long vector (i.e., if each connection is a row in a matrix, CADET wants this matrix in row-major storage). -Moreover, we have to specify the section in which the specified connectivity should be applied. - -The elements of a connection are (in order): - - ``[UnitOpID from, UnitOpID to, Component from, Component to, Volumetric flow rate]`` - -Usually, ``Component from`` and ``Component to`` can be set to ``-1``, which will connect all components from the origin and destination unit operations. - -.. note:: Since CADET version 4.1, the flow rates can also be defined with piecewise cubic polynomials. - Also, for the 2D General rate model inlet ports need to be speciefied. - For more information on the parameters, see the :ref:`file format specification `. - -In this case, we connect all components of ``unit_000`` to ``unit_001``, and from ``unit_001`` to ``unit_002``. +The connectivity of unit operations is defined in the ``FlowSheet`` class. +This class provides a directed graph structure that allows for the simple definition of configurations for multiple columns or reactor-separator networks, even when they are cyclic. +We add the previously defined units to the flow sheet and add connections between them. .. literalinclude:: ../../examples/breakthrough.py - :lines: 84-88 + :lines: 55-64 .. note:: Since the flow in the column models is incompressible, the total entering flow rate must equal the total outgoing flow rate. This restriction does not apply to a :ref:`CSTR model `, because it has a variable volume. -3. Setting Up the Simulator and Running the Simulation ------------------------------------------------------- - -Before we can start the simulation, we have to specify some settings for the simulator. - -First, we set some options for the solver and the time integrator. -Usually, these only need to be adapted in special cases. - -.. literalinclude:: ../../examples/breakthrough.py - :lines: 91-104 - -Of these options, the most interesting ones are ``time_integrator.abstol`` and ``time_integrator.reltol``, which control the errors during time integration, and ``nthreads``, which sets the number of CPU cores CADET is allowed to use. -Second, we have to specify which results we want CADET to return. -For this, we have to specify the ``/input/return/`` group. -For more information, see the :ref:`file format specification `. - -.. note::Because ``return`` is a reserved keyword in Python, we cannot use dot-notation but have to use the ‘proper’ dictionary indexing syntax. - -In this example, we want to write the concentration profile of the inlet and outlet of each unit operation. -In addition, we are interested in the concentration in the interstitial volume (bulk volume) of the column. +Process properties +^^^^^^^^^^^^^^^^^^^ +The ``Process`` class is used to define dynamic changes of model parameters or flow sheet connections. +This includes the duration of a simulation (``cycle_time``). +To instantiate a ``Process``, a ``FlowSheet`` needs to be passed as argument, as well as a string to name that process. .. literalinclude:: ../../examples/breakthrough.py - :lines: 106-115 + :lines: 67-70 -Finally, we have to set the time points at which we want to evaluate the solution. -Note that the end time must not exceed the last section time specified in the model. -If the time points are not set explicitly, the time integrator outputs the solution at arbitrary time points between ``0`` and ``section_times[-1]``. -.. literalinclude:: ../../examples/breakthrough.py - :lines: 117-118 +3. Setting Up the Simulator and Running the Simulation +------------------------------------------------------ -The last remaining step is to actually run the simulation. -For this, we have to specify a filename, save the configuration to ``H5``-format and call call the ``model``\ ’s ``run()`` function. -We check if the simulation has completed successfully and load the results. +To simulate a ``Process``, a simulator needs to be configured. +The simulator translates the ``Process`` configuration into the API of the corresponding simulator. .. literalinclude:: ../../examples/breakthrough.py - :lines: 121-131 + :lines: 72-76 4. Plotting the Results ----------------------- -The data is stored in the ``/output/`` group of the ``Cadet`` object. -The structure and format of the data is described in the :ref:`file format specification `. +The data is stored in the ``.solution`` group of the ``SimulationResults`` object. Finally, we plot the concentration signal at the outlet of the column. .. literalinclude:: ../../examples/breakthrough.py - :lines: 134-141 + :lines: 78 .. image:: _images/breakthrough_chromatogram.png - -Exercises ---------- - -- Add a second inlet section from ``10000`` to ``40000`` seconds in which no sample is fed into the column (rectangular pulse). -- Increase the length of the column and the flow rate. -- Increase the desorption coefficient ``MCL_KD``. -- Add a second component. -- Plot the concentration profile of the ``INLET`` unit operation +For further details on the front-end and more examples please refer to the `CADET-Process `_ documentation. diff --git a/master/developer_guide/build_options.html b/master/developer_guide/build_options.html index 27464c069..f13a0aaee 100644 --- a/master/developer_guide/build_options.html +++ b/master/developer_guide/build_options.html @@ -47,6 +47,7 @@

      Navigation

    • Simulation
    • Interface specifications
    • Developer Guide
        +
      • CADET-Python Introduction
      • Software Architecture
      • CADET build options
        • cmakeSettings.json
        • @@ -106,7 +107,7 @@

          Branches

          -

          CADET build options

          +

          CADET build options

          For builds on MS Windows, the CMake command arguments are specified for every build configuration in the cmakeSettings.json. For builds on Linux and MacOs, the CMake command arguments must be specified from the command line.

          diff --git a/master/developer_guide/cadet_core_architecture.html b/master/developer_guide/cadet_core_architecture.html index 49d78b4de..b5b9debc0 100644 --- a/master/developer_guide/cadet_core_architecture.html +++ b/master/developer_guide/cadet_core_architecture.html @@ -17,7 +17,7 @@ - + @@ -48,6 +48,7 @@

          Navigation

        • Simulation
        • Interface specifications
        • Developer Guide
            +
          • CADET-Python Introduction
          • Software Architecture
            • Features and Capabilities
            • Implementation Details
            • @@ -107,7 +108,7 @@

              Branches

              -

              Software Architecture

              +

              Software Architecture

              This section gives a general overview of the object-oriented c++ implementation of CADET-Core and is based on the Software Architecture chapter 3.2 in Samuel Lewekes PhD thesis [1].

              The CADET-Core software is designed to be modular, extendable, maintainable and computationally efficient and robust. To promote these goals, CADET-Core is implemented in C++, a highly performant, object-oriented language that supports cross-platform compatibility.

              @@ -129,12 +130,11 @@

              Features and Capabilities

              Implementation Details

              -

              Classes and realationships -Include figure 3.4 and/or 3.6 from Sams Diss

              +

              Classes and realationships

              ../_images/architecture_libcadet_classes.png
              -

              Fig. 13 Selected relationships of classes in libcadet [1].

              +

              Fig. 14 Selected relationships of classes in libcadet [1].

              ../_images/time_integration.png
              -

              Fig. 7 General time integration procedure

              +

              Fig. 8 General time integration procedure

              -

              The general control flow of a simulation is shown in Fig. 7. +

              The general control flow of a simulation is shown in Fig. 8. Some aspects of the tasks involved are discussed below.

              Time sections and transitions

              @@ -133,14 +133,14 @@

              Branches

              t_0 < t_1 < \dots < t_i < t_{i+1} < \dots < t_{\text{end}}. \end{aligned}\]

              Time sections are used for various purposes, for example, for defining piecewise polynomials used as inlet profiles or external function, for changing operating conditions such as flow rates, or for changing the connectivity in a network of unit operations. -A sequence of (one or more) time sections with smooth transitions is called a time slice (see Fig. 8).

              +A sequence of (one or more) time sections with smooth transitions is called a time slice (see Fig. 9).

              A transition from one section to the next can either be smooth or discontinuous. On smooth transitions, the time integrator can just step over the section transition. Contrary to smooth transitions, a discontinuous transition requires some extra work in resetting the time integrator and finding consistent initial conditions for the next time slice.

              -../_images/sections1.png +../_images/sections.png
              -

              Fig. 8 Time sections, time slices, and transitions between them

              +

              Fig. 9 Time sections, time slices, and transitions between them

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              Releases

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