The pearl_chain module#

Evaluate finite-life scatter with the pearl chain method.

The module shifts fracture tests to one normalized load level and fits their failure probabilities in log-cycle direction.

class pylife.materialdata.woehler.pearl_chain.PearlChainProbability(fractures, slope)[source]#

Shift fracture data to a normalized load level.

The pearl chain method moves fracture test results along a Wöhler slope to a common load level. Rossow cumulative failure probabilities are then assigned to the sorted shifted cycle numbers and fitted in a probability net. The fit is used to derive the scatter in cycle direction TN.

Parameters:

  • fractures (pandas.DataFrame) – Fracture test data with load and cycles columns.

  • slope (float) – Slope used to shift the fracture tests in double-logarithmic Wöhler space. The elementary analyzer passes the fitted regression slope.

Notes

The method is commonly used for DIN 50100-style Wöhler evaluations when fracture points at several load levels need to be represented by one probability distribution in cycle direction.

property normed_cycles#

Return the cycle numbers shifted to normed_load.

property normed_load#

Return the normalized load level.