Weight¶

Calculation of weight related aircraft metrics is straightforward, if OEW, MTOW and the passenger exit limit are known.

Imports¶

In [1]:

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

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

In [2]:

from aircraftdetective.processing.literature import process_data_weinold_database
from aircraftdetective.calculations.weight import calculate_weight_metrics

from aircraftdetective.processing.literature import process_data_weinold_database from aircraftdetective.calculations.weight import calculate_weight_metrics

Data Processing¶

In [3]:

df_acft = process_data_weinold_database()
df_acft = calculate_weight_metrics(df_acft)

df_acft = process_data_weinold_database() df_acft = calculate_weight_metrics(df_acft)

In [4]:

df_acft.head(5)

df_acft.head(5)

Out[4]:

	Manufacturer	Aircraft Designation	Aircraft Designation (Literature)	Aircraft Designation (aircraft-database.com)	Aircraft Designation (US DOT Schedule T2)	Type	YOI	Engine Designation (ICAO)	Engine Designation (aircraft-database.com)	Design Range	...	Sources (Weights)	Comments	Payload/Range: Range at Point B	Payload/Range: Range at Point C	Payload/Range: MZFW at Point B	Payload/Range: MZFW at Point C	Payload/Range: MTOW	Source (Payload/Range)	OEW/MTOW	OEW/Exit Limit
0	Airbus	A220-100	NaN	A220-100	A200-100 BD-500-1A10	Narrow	2016	PW1519G	PW1519G	6700.0	...	https://aircraft.airbus.com/sites/g/files/jlcb...	NaN	3598.3749284019223	7158.606627935522	50350.0026357575	43169.9977927272	60781.0	https://aircraft.airbus.com/sites/g/files/jlcb...	0.558161648177496	293.5
1	Airbus	A220-300	NaN	A220-300	A220-300 BD-500-1A11	Narrow	2016	PW1521G	PW1521G	6300.0	...	https://aircraft.airbus.com/sites/g/files/jlcb...	NaN	3681.3845400518944	6230.448593959429	55791.8615	49986.0186311349	67585.0	https://aircraft.airbus.com/sites/g/files/jlcb...	0.5229901269393512	264.85714285714283
2	Airbus	A300-600	A300-600	A300 B4-600	Airbus Industrie A300-600/R/CF/RCF	Wide	1984	CF6-80C2A5	CF6-80C2A5	6852.0	...	[JAWA:07/08]	NaN	3621.6888888888893	5700.044444444445	129255.84717830301	115645.08717830303	165035.00191999998	https://www.airbus.com/sites/g/files/jlcbta136...	0.4800606060606061	219.41828254847644
3	Airbus	A300-600	A300-600	A300 B4-601	Airbus Industrie A300-600/R/CF/RCF	Wide	1986	PW4158	PW4158	6852.0	...	[JAWA:07/08]	NaN	3621.6888888888893	5700.044444444445	129255.84717830301	115645.08717830303	165035.00191999998	https://www.airbus.com/sites/g/files/jlcbta136...	0.4797030303030303	219.25484764542935
4	Airbus	A310-200	NaN	A310-200	Airbus Industrie A310-200C/F	Wide	1983	JT9D-7R4D*	JT9D-7R4D*	6500.0	...	[JAWA:07/08]	NaN	nan	nan	nan	nan	nan	https://www.airbus.com/sites/g/files/jlcbta136...	0.5375	281.45454545454544

5 rows × 33 columns

Visualization¶

In [5]:

fig = go.Figure()
type_color_map = {'Narrow': 'blue', 'Wide': 'red', 'Regional': 'green'}
marker_colors = df_acft['Type'].map(type_color_map)

for typ, col in type_color_map.items():
    df_t = df_acft[df_acft['Type'] == typ]
    if df_t.empty:
        continue
    fig.add_trace(go.Scatter(
        x=df_t['YOI'],
        y=df_t['OEW/Exit Limit'].pint.magnitude,
        mode='markers',
        marker=dict(opacity=0.7, color=col),
        name=typ,
        showlegend=True,
        text=df_t['Aircraft Designation'],
    ))
fig.update_layout(
    xaxis_title="Year of Introduction (YOI)",
    yaxis_title="OEW/Exit Limit [kg]",
    legend_title_text="Type",
    legend=dict(
        x=0.01,
        y=0.01,
        xanchor='left',
        yanchor='bottom',
    )
)
fig.show(renderer="notebook")

fig = go.Figure() type_color_map = {'Narrow': 'blue', 'Wide': 'red', 'Regional': 'green'} marker_colors = df_acft['Type'].map(type_color_map) for typ, col in type_color_map.items(): df_t = df_acft[df_acft['Type'] == typ] if df_t.empty: continue fig.add_trace(go.Scatter( x=df_t['YOI'], y=df_t['OEW/Exit Limit'].pint.magnitude, mode='markers', marker=dict(opacity=0.7, color=col), name=typ, showlegend=True, text=df_t['Aircraft Designation'], )) fig.update_layout( xaxis_title="Year of Introduction (YOI)", yaxis_title="OEW/Exit Limit [kg]", legend_title_text="Type", legend=dict( x=0.01, y=0.01, xanchor='left', yanchor='bottom', ) ) fig.show(renderer="notebook")