shrinking.py

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r"""
Contains functionality to compensate shrinking and creep.
\author Bertram Richter
\date 2022
"""
 
import numpy as np
import scipy.signal
 
from . import compensator
 
class ShrinkCompensator(compensator.Compensator):
    r"""
    Implements compensation for shrink and creeping of concrete.
    """
    def __init__(self,
            method: str = "mean_min",
            *args, **kwargs):
        r"""
        Constructs a ShrinkCompensator object.
        \param method \copybrief method For more, see \ref method.
        \param args \copybrief args For more, see \ref args.
        \param kwargs \copybrief kwargs For more, see \ref kwargs.
        """
        
        self.method = method
        
        self.args = args
        
        self.kwargs = kwargs
    def run(self, x: np.array, strain: np.array, strain_inst: np.array) -> np.array:
            r"""
            The influence of concrete creep and shrinking is calculated.
            All of the parameters are assumed to be in sync and sanitized.
            \param x Positional data.
            \param strain Strain data, belonging to `x`, that was measured with time delay after applying the load.
            \param strain_inst Instantaneous strain belonging to `x`, that appear right after applying the load to the structure.
            \return Returns an array of same length as the given arrays.
            """
            assert all(entry is not None for entry in [x, strain, strain_inst]), "Can not compute shrink compensation. At least one of `x`, `strain` and `strain_inst` is None! Please provide all of them!"
            peaks_min, properties = scipy.signal.find_peaks(-strain_inst, *self.args, **self.kwargs)
            strain_min_inst = np.array([strain_inst[i] for i in peaks_min])
            strain_min = np.array([strain[i] for i in peaks_min])
            min_diff = np.mean(strain_min - strain_min_inst)
            shrink_calibration_values = np.full(len(x), min_diff)
            return shrink_calibration_values