Add ports / MCT Model

[schmoelder]

This PR adds ports to UnitOperations in CADET process which are required by models such as the 2D-GRM.

For starters, we will test this with the Multi-Channel Transport-Model

To fix #3, we also need to fix #70.

To do

• Add ports to add_connection method
• Add discretization class for MCT
• Add SolutionRecorder for MCT
• Store connections with ports in FlowSheet
  • Add tests
  • How to expose discretization n_rad to flow_sheet/ports
• Add check methods
  • Unconnected ports
  • Changes in discretization configuration
  • flow rate balance
• Open question: Should ports have individual output states?
• Add parameters to the Name Converter for the MCT in cadetAdapter
• Create a SizedMatrix Type and/or check SizednDArray if it meets our requirements
• Add MCT tests in test_unit_operation
  • add create_MCT
• In unitOperation change flow_direction into array of Switches
• Check dimensionality for all unit operations, see also in solution

Open question

Should the MCT (and other potential 2D models) inherit from TubularReactor? How would this look like.
Should every channel of the MCT have a port by default?

[schmoelder]

Ok, I can now setup an MCT unit operation. We should still test whether all parameters are transferred correctly to CADET in the CadetAdapter.

Next steps should address the ports. Please add some tests so that we have something to work with. Also, we should work on adding the multiplex features (see #70).

[schmoelder]

After some brainstorming, @hannahlanzrath and I tried to come up with some better structure for storing connections. Here are some general ideas.

CASE 1:
    - Inlet
    - Outlet

_connections['inlet'] = Dict({
    'origins': [],
    'destinations': ['outlet'],
})

_connections['outlet'] = Dict({
    'origins': ['inlet'],
    'destinations': [],
})


CASE 2: No ports
    - Inlet 1
    - Inlet 2
    - Column
    - Outlet

_connections['inlet_1'] = Dict({
    'origins': [],
    'destinations': ['mct'],
})

_connections['inlet_2'] = Dict({
    'origins': ['column'],
    'destinations': [],
})

_connections['column'] = Dict({
    'origins': ['inlet_1', 'inlet_2'],
    'destinations': ['outlet'],
})

_connections['outlet'] = Dict({
    'origins': ['column'],
    'destinations': [],
})


CASE 3a: With ports # Option 1; distinguish between ports and no ports
    - Inlet 1
    - Inlet 2
    - MCT
    - Outlet

_connections['inlet_1'] = Dict({
    'origins': [],
    'destinations': {
        'mct': [0],
    }
})

_connections['inlet_2'] = Dict({
    'origins': [],
    'destinations': {
        'mct': [1],
    }
})

_connections['mct'] = Dict({
    'origins': {
        0:
            'inlet_1': None,
        },
        1: {
            'inlet_2': None,
        }
    },
    'destinations': {
        0: {
            'outlet': None,
        },
        1: {
            'outlet': None,
        }
    }
})

_connections['outlet'] = Dict({
    'origins': {
        'mct': [0, 1],
    },
    'destinations': [],
})

    'origins': [('mct', 0), ('mct', 1)]


    'origins': ['inlet_1', ('mct', 0), ('mct', 1), 'inlet_2']

CASE 3b: With ports # Option 1; distinguish between ports and no ports
    - Inlet 1
    - Inlet 2
    - MCT
    - Outlet

_connections['inlet_1'] = Dict({
    'origins': [],
    'destinations': {
        'mct': [0],
    }
})

_connections['inlet_2'] = Dict({
    'origins': [],
    'destinations': {
        'mct': [1],
    }
})

_connections['mct'] = Dict({
    'origins': {
        0: {
            'inlet_1': None,
        },
        1: {
            'inlet_2': None,
        }
    },
    'destinations': {
        0: {
            'outlet': None,
        },
        1: {
            'outlet': None,
        }
    }
})

_connections['outlet'] = Dict({
    'origins': {
        'mct': [0, 1],
    },
    'destinations': [],
})


CASE 4: With ports # Option 1; All units have ports (some only one)
    - Inlet 1
    - Inlet 2
    - MCT
    - Outlet

_connections['inlet_1'] = Dict({
    'origins': None,
    'destinations': {
        0: {
            'mct': [0],
        },
    },
})

_connections['inlet_2'] = Dict({
    'origins': None,
    'destinations': {
        0: {
            'mct': [1],
        },
    },
})

_connections['mct'] = Dict({
    'origins': {
        0: {
            'inlet_1': [0],
        },
        1: {
            'inlet_2': [0],
        }
    },
    'destinations': {
        0: {
            'outlet': [0],
        },
        1: {
            'outlet': [0],
        }
    }
})

_connections['outlet'] = Dict({
    'origins': {
        0: {
            'mct': [0, 1],
        },
    },
    'destinations': None,
})

For now, we went with Case 4. We'll see how this works out when having to calculate flow rates.

[hannahlanzrath]

Test cases for the MCT

[schmoelder]

We should consider moving this outside the Test_Unit_Operation class definition s.t. we could potentially reuse the same fixture for other tests.

(Same goes for all other units / binding / reaction models)

[schmoelder]

because a Cstr has no spatial discretization. In fact, its core assumption is a spatial homogeneity.

[schmoelder]

please remove the white space.

[schmoelder]

Remove code that is commented out or add TODO flag.

[schmoelder]

Sorry, merged the wrong branch. 😓