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Fix high linear fuel flow scaling in models and tests #1296

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Fix high linear fuel flow scaling in models and tests #1296

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6ac78b0
fixed high linear scaling factor in models & tests
jkirk5 Sep 4, 2026
2e81b3b
added success requirement to throttle allocation bench
jkirk5 Sep 4, 2026
b031161
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jkirk5 Sep 4, 2026
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2 changes: 1 addition & 1 deletion aviary/models/aircraft/advanced_single_aisle/advanced_single_aisle_FLOPS.csv
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Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ aircraft:engine:flight_idle_max_fraction,1,unitless
aircraft:engine:flight_idle_min_fraction,0.08,unitless
aircraft:engine:flight_idle_thrust_fraction,0,unitless
aircraft:engine:fuel_flow_scaler_constant_term,0,unitless
aircraft:engine:fuel_flow_scaler_linear_term,1,unitless
aircraft:engine:fuel_flow_scaler_linear_term,0,unitless
aircraft:engine:generate_flight_idle,True,unitless
aircraft:engine:geopotential_alt,False,unitless
aircraft:engine:ignore_negative_thrust,False,unitless
Expand Down
45 changes: 24 additions & 21 deletions aviary/subsystems/propulsion/test/test_engine_scaling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
import numpy as np
import openmdao.api as om
from openmdao.utils.assert_utils import assert_check_partials, assert_near_equal
from openmdao.utils.testing_utils import use_tempdirs

from aviary.subsystems.propulsion.engine_deck import EngineDeck
from aviary.subsystems.propulsion.engine_scaling import EngineScaling
Expand All @@ -16,14 +17,13 @@

class EngineScalingTest(unittest.TestCase):
def setUp(self):
self.prob = om.Problem(model=om.Group())
self.prob = om.Problem()

def test_case(self):
nn = 4
count = 1

filename = 'models/engines/turbofan_28k.csv'
filename = get_path(filename)
filename = get_path('models/engines/turbofan_28k.csv')

options = AviaryValues()
options.set_val(Settings.VERBOSITY, 0)
Expand All @@ -32,7 +32,7 @@ def test_case(self):
# make supersonic scaling factor extremely high so it is obvious if it gets used
options.set_val(Aircraft.Engine.SUPERSONIC_FUEL_FLOW_SCALER, 1000)
options.set_val(Aircraft.Engine.FUEL_FLOW_SCALER_CONSTANT_TERM, 1.15)
options.set_val(Aircraft.Engine.FUEL_FLOW_SCALER_LINEAR_TERM, 1.05)
options.set_val(Aircraft.Engine.FUEL_FLOW_SCALER_LINEAR_TERM, 0.05)
options.set_val(Aircraft.Engine.CONSTANT_FUEL_MASS_CONSUMPTION, 10.0, units='lbm/h')
options.set_val(Aircraft.Engine.SCALE_FACTOR, 0.9)
options.set_val(Aircraft.Engine.GENERATE_FLIGHT_IDLE, True)
Expand All @@ -43,10 +43,8 @@ def test_case(self):
options.set_val(Aircraft.Engine.GEOPOTENTIAL_ALT, False)
options.set_val(Aircraft.Engine.INTERPOLATION_METHOD, 'slinear')

# engine1 uses all scaling factors
engine1 = EngineDeck(options=options)

preprocess_propulsion(options, [engine1])
engine = EngineDeck(options=options)
preprocess_propulsion(options, [engine])

engine_variables = {
EngineModelVariables.THRUST: 'lbf',
Expand Down Expand Up @@ -74,20 +72,25 @@ def test_case(self):

self.prob.run_model()

thrust = self.prob.get_val(Dynamic.Vehicle.Propulsion.THRUST)
fuel_flow = self.prob.get_val(Dynamic.Vehicle.Propulsion.FUEL_MASS_FLOW_RATE_NEGATIVE)
nox_rate = self.prob.get_val(Dynamic.Vehicle.Propulsion.NOX_RATE)
# exit_area = self.prob.get_val(Dynamic.Mission.EXIT_AREA)

thrust_expected = np.array([900.0, 900.0, 900.0, 900])

fuel_flow_expected = np.array([-1836.55, -1836.55, -1836.55, -1836.55])

nox_rate_expected = np.array([9.0, 9.0, 9.0, 9])
expected_values = {
Dynamic.Vehicle.Propulsion.THRUST: (
np.array([900.0, 900.0, 900.0, 900.0]),
'lbf',
),
Dynamic.Vehicle.Propulsion.FUEL_MASS_FLOW_RATE_NEGATIVE: (
np.array([-1755.55, -1755.55, -1755.55, -1755.55]),
'lbm/h',
),
Dynamic.Vehicle.Propulsion.NOX_RATE: (
np.array([9.0, 9.0, 9.0, 9.0]),
'lbm/h',
),
}

assert_near_equal(thrust, thrust_expected, tolerance=1e-10)
assert_near_equal(fuel_flow, fuel_flow_expected, tolerance=1e-10)
assert_near_equal(nox_rate, nox_rate_expected, tolerance=1e-10)
for var_name, (expected, units) in expected_values.items():
with self.subTest(var=var_name):
actual = self.prob.get_val(var_name, units=units)
assert_near_equal(actual, expected, tolerance=1e-10)

partial_data = self.prob.check_partials(out_stream=None, method='cs')
assert_check_partials(partial_data, atol=1e-11, rtol=1e-10)
Expand Down
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