In this study, the monotonic and cyclic material properties of steel material of medium static strength produced additively in the wire arc additive manufacturing (WAAM) process were investigated. This investigated material is expected to be particularly applicable to the field of mechanical engineering, for which practical applications of the WAAM process are still pending and for which hardly any characteristic values can be found in the literature so far. The focus of the investigation was, on the one hand, to determine how the material characteristics are influenced by the load direction in relation to the layered structure and, on the other hand, how they are affected by different interlayer temperatures. For this purpose, monotonic tensile tests were carried out at room temperature as well as at elevated temperatures, and the cyclic material properties were determined. In addition, the hardness of the material and the residual stresses induced during production were measured and compared. In addition to the provision of characteristic properties for the investigated material, it was aimed to determine the extent to which the interlayer temperature influences the strength characteristics, since this can have a considerable influence on the production times and, thus, the economic efficiency of the process.

The prediction of fatigue lives of metallic components using the notch strain approach is based on local stresses and strains. These can be determined either by analytical approximation formulas such as Neuber's rule based on linear elastic stresses or by finite element analysis with elastic–plastic material behavior. The latter has the disadvantage of longer computation times.This paper discusses a draft for application of artificial neural networks as an alternative approach for estimating uniaxial and multiaxial proportional elastic–plastic stresses and strains in notch roots based on linear elastic stresses. These networks are trained on results from elastic–plastic finite element analyses on flat bars notched on both sides and circumferentially notched shafts to predict local stresses. The resulting accuracy is compared to the analytical approximation formulas.The research findings confirm that neural networks can estimate local stresses with similar scatter and better mean value compared to analytical formulas.

Tests under variable amplitude loading on self‐piercing riveted components with semi‐tubular rivets result in longer service lives than those calculated by linear damage accumulation. An overview of the literature shows that damage sums greater than one are found for other types of riveted joints either, while an explanation for this unusual behavior is still missing. Therefore, this behavior is examined in more detail. A correlation is shown between the damage sum and the hardness of the load spectrum. Considering this correlation, the accuracy of the service life estimation can be improved significantly.

An estimation of the elastic-plastic stress state using elasticity-theoretical input data is an essential part of the service life estimation with the local strain approach in general and a German guideline based on it, in particular. This guideline uses two different notch root approximations (an extended version of Neuber’s rule and an approach according to Seeger and Beste) for this estimation. Both require the implementation of Newton’s method to be iteratively solved. However, many options are left open to the user concerning implementation in program code. This paper discusses ways in which notch root approximation methods can be implemented efficiently for use in software systems and elaborates an application recommendation. The following aspects and their influence on the computational accuracy and performance of Newton’s method are considered in detail: influence of the formulation of the root finding problem, determination of the derivative required for Newton’s method and influence of the termination criterion. The investigation shows that the advice given in the abovementioned guideline indeed leads to a conservative implementation. By carefully considering the investigated aspects, however, the computational performance can be increased by approximately a factor of 2–3 without influencing the accuracy of the service life estimation.

For the service life estimation of metallic components under cyclic loading according to strain-based approaches, a simulation of the elastic-plastic stress–strain path at the point of interest is necessary. An efficient method for determining this stress–strain path is the use of the load–notch-strain curve, as this is also implemented within the FKM guideline nonlinear. The load–notch-strain curve describes the relationship between the load on the component and the local elastic-plastic strain. On the one hand, this can be estimated from loads or theoretical elastic stresses by using notch root approximations. On the other hand, this can be determined in a finite element analysis based on the elastic-plastic material behaviour. This contribution describes how this latter option is carried out in general and how it can be optimised in such a way that the FEA requires significantly less calculation time. To show the benefit of this optimisation, a comparative calculation on an exemplary geometry is carried out.