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aeromaps.models.impacts.life_cycle_assessment.life_cycle_assessment_default

Default model for Life Cycle Assessment (LCA) of air transportation systems

LifeCycleAssessmentDefault 

LifeCycleAssessmentDefault(name='life_cycle_assessment_default', json_file=None, split_by=None, *args, **kwargs)

Bases: AeroMAPSModel

Model to load LCA pre-compiled expressions from a JSON file. Compared to the LifeCycleAssessmentCustom model, this model does not require the user to install LCA-specific packages and is disconnected from the ecoinvent database. It is therefore easier to use and deploy, but less flexible as the user cannot modify the LCA model structure.

Parameters:

Name Type Description Default
name str

Name of the model instance.

 'life_cycle_assessment_default'
json_file str

Path to the JSON file containing the pre-compiled LCA model.

 None
split_by str

Axis to split the results by (e.g., "phase"). If None, total results are provided.

 None

Attributes:

Name Type Description
model Model

The LCA model loaded from the JSON file.
methods List[tuple]

List of impact assessment methods available in the model.
axis_keys List[str] or None

List of keys for the specified axis, if applicable.
params_names List[str]

List of parameter names required by the LCA model.
xarray_lca DataArray

Xarray DataArray storing the LCA results after computation.
Source code in aeromaps/models/impacts/life_cycle_assessment/life_cycle_assessment_default.py 
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def __init__(
    self,
    name: str = "life_cycle_assessment_default",
    json_file: str = None,
    split_by: str = None,
    *args,
    **kwargs,
):
    super().__init__(
        name=name,
        model_type="custom",
        # inputs/outputs are defined in __init__ rather than auto generated from compute() signature
        *args,
        **kwargs,
    )

    # Instantiate LCA model from JSON file
    if json_file is None:
        raise ValueError("JSON file is missing.")

    # Get methods names, axis keys, and parameters names
    self.axis = split_by if split_by else TOTAL_AXIS_KEY

    print("===== LCA Default Model Import =====")
    self.model = Model.from_file(json_file, axis=self.axis, progress_bar=True)
    self.methods = [ast.literal_eval(s) for s in self.model.impacts.keys()]
    self.axis_keys = None
    expr = self.model.expressions[self.axis][str(self.methods[0])].expr
    if isinstance(expr, dict):
        self.axis_keys = list(expr.keys())
    self.params_names = list(self.model.params.keys())
    print("====================================")

    # Initialize empty xarray to store results after compute
    self.xarray_lca = xr.DataArray()

    # --- Add LCA parameters as inputs of this AeroMAPSModel ---
    self._skip_data_type_validation = True  # see aeromaps/core/gemseo.py
    self.input_names = []
    self.output_names = []

    for x in self.params_names:
        # Years of simulation are directly taken from AeroMAPS timeline and not as an input parameter
        if x == KEY_YEAR:
            continue

        self.input_names.append(x)
        self.input_names.append(x + "_reference_years")
        self.input_names.append(x + "_reference_years_values")

        self.default_input_data[x] = np.nan
        self.default_input_data[x + "_reference_years"] = np.nan
        self.default_input_data[x + "_reference_years_values"] = np.nan

    # --- Add LCA impact categories the outputs to the AeroMAPSModel ---
    if self.axis_keys:
        for method in self.methods:
            for phase in self.axis_keys:
                method_with_axis = method + (phase,)
                self.output_names.append(tuple_to_varname(method_with_axis))
    else:
        for method in self.methods:
            self.output_names.append(tuple_to_varname(method))

compute 

compute(input_data)

Main compute method for the LCA model.

Parameters:

Name Type Description Default
input_data dict

Dictionary containing input parameter values.

 required

Returns:

Name Type Description
output_data dict

Dictionary containing LCA results as pd.Series for each impact category.
Source code in aeromaps/models/impacts/life_cycle_assessment/life_cycle_assessment_default.py 
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def compute(self, input_data) -> dict:
    """
    Main compute method for the LCA model.

    Parameters
    ----------
    input_data : dict
        Dictionary containing input parameter values.

    Returns
    -------
    output_data : dict
        Dictionary containing LCA results as pd.Series for each impact category.
    """
    # --- Assign values to parameters ---
    params_dict = self._get_param_values(input_data)

    # --- Calculate impacts for all parameters at once ---
    res = self._multi_lca_algebraic_json(**params_dict)

    # --- Store xarray to enable user to access data after process calculation ---
    res["params"] = params_dict[KEY_YEAR]  # replace param index by actual years
    res = res.rename({"params": KEY_YEAR})  # rename 'params' dimension to 'year'
    self.xarray_lca = res

    # --- Convert xarray to pd.Series to enable connection with other models ---
    output_data = self._convert_xarray_to_series(res)
    self._store_outputs(output_data)

    return output_data