Abstract
The recently proposed multiaxial racetrack filter (MRF) is able to deal with general non-proportional multiaxial load histories. While only requiring a single user-defined scalar filter amplitude, the MRF is able to synchronously eliminate non-damaging events from any noisy multiaxial load history without changing the overall shape of its original path, a necessary condition to avoid introducing errors in fatigue damage assessments. The MRF procedures are optimized here by the introduction of a pre-processing “partitioning” step on the load history data, which selects candidates for the reversal points in a robust partitioning process, highly increasing the filter efficiency and decreasing its computational time. The improved MRF is evaluated through the fatigue analyses of over-sampled tension-torsion data measured in 316L stainless steel tubular specimens under non-proportional load paths.
Highlights
INTRODUCTIONF atigue load histories measured under actual field conditions usually are noisy, over-sampled, and contain too many non-damaging low-amplitude events that can largely increase the subsequent fatigue damage calculation burden
A most important practical issue in multiaxial fatigue analyses is how to reduce a large amount of redundant multiaxial data to a manageable size to decrease their intrinsically high computational cost, while maintaining all the essential features of the load history that contribute to plasticity memory effects
Despite being highly filtered, the optimized multiaxial racetrack filter (MRF) outputs can almost exactly describe the original multiaxial load history, capturing all reversal points and the load path shape, which is a most important feature for path-equivalent range calculations used in fatigue damage assessments
Summary
F atigue load histories measured under actual field conditions usually are noisy, over-sampled, and contain too many non-damaging low-amplitude events that can largely increase the subsequent fatigue damage calculation burden. The MRF requires a user-defined scalar filter amplitude r, which is graphically represented in Fig. 1 as the radius of the small dashed circle centered at point 1 In this example, r 80MPa was chosen as the amplitude, which in the x xy 3 space has a clear physical meaning: r is the Mises distance between two stress states, due to the adopted 3 scaling factor used in the shear component. The MRF algorithm, thoroughly described in [10,11,12,13], was able to reduce the 238 oversampled measurements to only 8, guaranteeing that no filtered-out data lies beyond r 80MPa of the resulting polygonal path 1-2-3-4-5-6-7-8-1 This filtering process results in a dramatic decrease of the computational time needed for further multiaxial fatigue life calculations, especially considering that the original 238 points were from a single elliptical path. A more efficient way is proposed where a preprocessing “partitioning” operation is performed on the original sampled points, resulting in a better description of the path with fewer data points
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