Engines¶

Imports¶

In [8]:

import pandas as pd
import numpy as np
import pint
ureg = pint.get_application_registry()
import plotly.graph_objects as go

import pandas as pd import numpy as np import pint ureg = pint.get_application_registry() import plotly.graph_objects as go

In [9]:

from aircraftdetective.processing.acftdb import _read_engine_database
from aircraftdetective.processing.literature import (
    process_data_weinold_database,
)

from aircraftdetective.calculations.engines import (
    determine_takeoff_to_cruise_tsfc_ratio,
    scale_engine_data_from_icao_emissions_database
)

from aircraftdetective.utility.tabular import (
    left_merge_wildcard,
)
from aircraftdetective.utility.tabular import update_column_data

from aircraftdetective.processing.acftdb import _read_engine_database from aircraftdetective.processing.literature import ( process_data_weinold_database, ) from aircraftdetective.calculations.engines import ( determine_takeoff_to_cruise_tsfc_ratio, scale_engine_data_from_icao_emissions_database ) from aircraftdetective.utility.tabular import ( left_merge_wildcard, ) from aircraftdetective.utility.tabular import update_column_data

Data Processing¶

In [10]:

df_acft = process_data_weinold_database()
df_engines_acftdb = _read_engine_database()
df_literature = process_data_weinold_database(sheet_name='Literature Data')

df_acft = process_data_weinold_database() df_engines_acftdb = _read_engine_database() df_literature = process_data_weinold_database(sheet_name='Literature Data')

In [33]:

dict_tsfc_scaling = determine_takeoff_to_cruise_tsfc_ratio(degree=2, plot=True)
df_engines_icao_scaled = scale_engine_data_from_icao_emissions_database(
    scaling_polynomial=dict_tsfc_scaling['TSFC (cruise)'],
)

dict_tsfc_scaling = determine_takeoff_to_cruise_tsfc_ratio(degree=2, plot=True) df_engines_icao_scaled = scale_engine_data_from_icao_emissions_database( scaling_polynomial=dict_tsfc_scaling['TSFC (cruise)'], )

In [39]:

dict_tsfc_scaling = determine_takeoff_to_cruise_tsfc_ratio(degree=4, plot=True)
df_engines_icao_scaled = scale_engine_data_from_icao_emissions_database(
    scaling_polynomial=dict_tsfc_scaling['TSFC (cruise)'],
)

dict_tsfc_scaling = determine_takeoff_to_cruise_tsfc_ratio(degree=4, plot=True) df_engines_icao_scaled = scale_engine_data_from_icao_emissions_database( scaling_polynomial=dict_tsfc_scaling['TSFC (cruise)'], )

In [40]:

bpr = df_engines_icao_scaled['B/P Ratio'].astype(float)
colors = np.where(bpr < 2, 'red', np.where(bpr > 8, 'green', 'blue'))

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=df_engines_icao_scaled['TSFC (takeoff)'].pint.to('mg/(N*s)').pint.magnitude,
    y=df_engines_icao_scaled['TSFC (cruise)'].pint.to('mg/(N*s)').pint.magnitude,
    mode='markers',
    marker=dict(opacity=0.7, color=colors),
    text=df_engines_icao_scaled['Engine Identification'] + '/'+ df_engines_icao_scaled['Final Test Date'].astype(str),
    hovertemplate='Engine: %{text}<br>TSFC (takeoff): %{x}<br>TSFC (cruise): %{y:.2f}<br>BPR: %{marker.color}<extra></extra>'
))
fig.update_layout(
    xaxis_title="TSFC (takeoff) [g/(kN·s)]",
    yaxis_title="TSFC (cruise) [g/(kN·s)]"
)
fig.show(renderer="notebook")

bpr = df_engines_icao_scaled['B/P Ratio'].astype(float) colors = np.where(bpr < 2, 'red', np.where(bpr > 8, 'green', 'blue')) fig = go.Figure() fig.add_trace(go.Scatter( x=df_engines_icao_scaled['TSFC (takeoff)'].pint.to('mg/(N*s)').pint.magnitude, y=df_engines_icao_scaled['TSFC (cruise)'].pint.to('mg/(N*s)').pint.magnitude, mode='markers', marker=dict(opacity=0.7, color=colors), text=df_engines_icao_scaled['Engine Identification'] + '/'+ df_engines_icao_scaled['Final Test Date'].astype(str), hovertemplate='Engine: %{text}<br>TSFC (takeoff): %{x}<br>TSFC (cruise): %{y:.2f}<br>BPR: %{marker.color}<extra></extra>' )) fig.update_layout( xaxis_title="TSFC (takeoff) [g/(kN·s)]", yaxis_title="TSFC (cruise) [g/(kN·s)]" ) fig.show(renderer="notebook")

In [41]:

df_merged = left_merge_wildcard(
    df_left=df_acft,
    df_right=df_engines_icao_scaled,
    left_on='Engine Designation (ICAO)',
    right_on='Engine Identification',
)
df_merged = left_merge_wildcard(
    df_left=df_merged,
    df_right=df_engines_acftdb,
    left_on='Engine Designation (aircraft-database.com)',
    right_on='Engine Designation',
)
df_merged = update_column_data(
    df_main=df_merged,
    df_other=df_literature,
    merge_column='Aircraft Designation (Literature)',
    list_columns=['TSFC (cruise)'],
)

df_merged = left_merge_wildcard( df_left=df_acft, df_right=df_engines_icao_scaled, left_on='Engine Designation (ICAO)', right_on='Engine Identification', ) df_merged = left_merge_wildcard( df_left=df_merged, df_right=df_engines_acftdb, left_on='Engine Designation (aircraft-database.com)', right_on='Engine Designation', ) df_merged = update_column_data( df_main=df_merged, df_other=df_literature, merge_column='Aircraft Designation (Literature)', list_columns=['TSFC (cruise)'], )

Visualization¶

In [42]:

bpr = df_merged['B/P Ratio'].astype(float)
colors = np.where(bpr < 2, 'red', np.where(bpr > 8, 'green', 'blue'))

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=df_merged['YOI'].astype('int64'),
    y=df_merged['TSFC (cruise)'].pint.to('mg/(N*s)').pint.magnitude,
    mode='markers',
    marker=dict(opacity=0.7, color=colors),
    text=df_merged['Aircraft Designation'] + '/'+ df_merged['Engine Designation (ICAO)'],
    hovertemplate='Engine: %{text}<br>YOI: %{x}<br>TSFC (cruise): %{y:.2f}<br>BPR: %{marker.color}<extra></extra>'
))
fig.update_layout(
    xaxis_title="Year of Introduction (YOI)",
    yaxis_title="TSFC (cruise) [g/(kN·s)]"
)
fig.show(renderer="notebook")

bpr = df_merged['B/P Ratio'].astype(float) colors = np.where(bpr < 2, 'red', np.where(bpr > 8, 'green', 'blue')) fig = go.Figure() fig.add_trace(go.Scatter( x=df_merged['YOI'].astype('int64'), y=df_merged['TSFC (cruise)'].pint.to('mg/(N*s)').pint.magnitude, mode='markers', marker=dict(opacity=0.7, color=colors), text=df_merged['Aircraft Designation'] + '/'+ df_merged['Engine Designation (ICAO)'], hovertemplate='Engine: %{text}<br>YOI: %{x}<br>TSFC (cruise): %{y:.2f}<br>BPR: %{marker.color}<extra></extra>' )) fig.update_layout( xaxis_title="Year of Introduction (YOI)", yaxis_title="TSFC (cruise) [g/(kN·s)]" ) fig.show(renderer="notebook")