Up to now, no consistent fatigue assessment approach of powder metallurgy (PM) components is available. For some materials and for some parameters, such as the density, a relationship to the fatigue strength is known; however, for other materials, such relationships are unknown. Based on an extensive data set with 828 test series, the present work addresses this problem by conceiving and applying five machine learning (ML)-based approaches to increase the accuracy of the prediction of the fatigue life as well as to predict the scatter of unknown data as precisely as possible. With the elaborated procedure, on the one hand, a scatter range of T S ¼ 1 : 1:40 can be achieved on completely unknown data. On the other hand, by using a newly defined loss function, the standard deviation of unknown data can be predicted very accurately. The findings provide the basis for further research on cost and efficiency optimized design of PM components through better estimation of fatigue life.
In this study, we investigate the influence of control type and strain rate on the lifetime of specimens manufactured from 50CrMo4. This influence is described by a strain rate dependent method that uses cyclic stress strain curves to correct displacement-controlled cyclic test results. The objective of this correction is to eliminate the stress related differences between displacement-controlled cyclic test results and force-controlled cyclic test results. The method is applied to the results of ultrasonic fatigue tests of six different combinations of heat treatment, specimen geometry (notch factor) and atmosphere. In a statistical analysis, the corrected results show an improved agreement with test results obtained on conventional fatigue testing equipment with similar specimens: the standard deviation in combined data sets is significantly reduced (p = 4.1%). We discuss the literature on intrinsic and extrinsic strain rate effects in carbon steels.
In the European standards specifying disc spring manufacturing, geometry, shape and characteristic, an edge rounding is prescribed. Common methods for the calculation of disc spring characteristics, even in these standards, are based on a rectangular cross-section. This discrepancy can lead to a considerable divergence of the computed characteristic from the characteristic determined by testing. In literature, this divergence has not yet been examined with regard to rounded edges. In this paper, a new method addressing this problem is introduced. For this purpose, the geometry of idealized disc springs is parameterized. Based on four edge radii and two angles of the inner and outer faces, equations to compute the initial cone angle and the lever arm are introduced. These equations are used to formulate an algorithm to adapt other computation methods to non-rectangular cross-sections and rounded edges. The method is applied to the formulas by Almen–Laszlo, Curti–Orlando, Zheng and those by Kobelev. FE simulations of disc springs with rounded edges and a non-rectangular cross-section were used to verify the new formulas. The results show that the introduced method can be applied to known characteristic computation methods and result in a model expansion taking cross-section variations into account. The adjusted characteristics show more accurate alignment to the FE simulation for the cross-section variations investigated. These findings not only close the geometric gap between the manufacturing guidelines and the computation on an analytical basis, they also define a new parameter space for designs of disc springs and a corresponding force computation method to optimize spring characteristics.
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