Critical Plane Analysis
Critical plane analysis enables accurate calculation of the effects of multiaxial loading on fatigue performance. The analysis considers how a series of potential microcracks will experience the 6 components of the stress tensor. Each potential microcrack is identified by its unit normal vector, and the set of all unit normals is represented as a sphere colored according to the life computed for each normal. The shortest life among all of the normals (colored red in the image) is reported as the fatigue life and its location on the sphere shows the plane on which cracks first initiate. We developed and patented the first critical plane analysis for elastomers. Our algorithm considers the effects of finite straining and of crack closure.
Rubber’s macromolecular structure gives rise to unique behaviors that require appropriately specialized analysis methods. Endurica is the world leader in elastomer-specific technology for characterizing and analyzing elastomer durability.
Rainflow counting considers how variable amplitude loading will influence fatigue performance. The load signal experienced by each microcrack is first obtained via critical plane analysis. It is then parsed into a list of discrete events. Each event contributes to the total rate of crack development according to the crack growth rate law of the material. Our implementation includes an index back into the original time domain signal, so that the most damaging events can be quickly identified.
Nonlinear Material Behavior
Elastomers exhibit a rich set of behaviors. Physically realistic, nonlinear models are provided in our fatigue solver to represent cyclic stress-strain behavior, strain crystallization effects (or lack of), and time and temperature dependence. For each behavior, both minimalistic and high accuracy models are provided, giving analysts a high degree of control over analysis scope and accuracy.
Fatigue Testing Methods
Our 3rd generation testing methods reflect the state of the art in fatigue testing for elastomers. Traditional fatigue testing methods offer too little control over execution time and data scatter, and they indiscriminately confound various influences on fatigue performance. Our testing methods are designed to produce accurate results within a pre-specified time budget. They are physics-based and are optimized to give the best possible observation of each factor governing fatigue performance.