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# https://github.com/boschresearch/pylife
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
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__author__ = "Johannes Mueller"
__maintainer__ = __author__
import pandas as pd
from pylife.materiallaws import WoehlerCurve
[docs]
@pd.api.extensions.register_series_accessor('fatigue')
@pd.api.extensions.register_dataframe_accessor('fatigue')
class Fatigue(WoehlerCurve):
"""Extension for ``WoehlerCurve`` accessor class for fatigue calculations.
Note
----
This class is accessible by the ``fatigue`` accessor attribute.
"""
[docs]
def damage(self, load_collective):
"""Calculate the damage to the material caused by a given load collective.
Parameters
----------
load_collective : pandas object or object behaving like a load collective
The given load collective
Returns
-------
damage : :class:`pandas.Series`
The calculated damage values. The index is the broadcast between
``load_collective`` and ``self``.
"""
cycles = self.cycles(load_collective.amplitude)
return pd.Series(load_collective.cycles / cycles, name='damage')
[docs]
def security_load(self, load_distribution, allowed_failure_probability):
"""Calculate the security factor in load direction for given load distribution.
Parameters
----------
load_distribution : pandas object or object behaving like a load collective
The given load distribution
Returns
-------
security_factor : :class:`pandas.Series`
The calculated security_factors. The index is the broadcast between
``load_distribution`` and ``self``.
"""
allowed_load = self.load(load_distribution.cycles, allowed_failure_probability)
return pd.Series(allowed_load / load_distribution.amplitude, name='security_factor')
[docs]
def security_cycles(self, load_distribution, allowed_failure_probability):
"""Calculate the security factor in cycles direction for given load distribution.
Parameters
----------
load_distribution : pandas object or object behaving like a load collective
The given load distribution
Returns
-------
security_factor : :class:`pandas.Series`
The calculated security_factors. The index is the broadcast between
``load_distribution`` and ``self``.
"""
allowed_cycles = self.cycles(load_distribution.amplitude, allowed_failure_probability)
return pd.Series(allowed_cycles / load_distribution.cycles, name='security_factor')