Within the scope of this research, a new short-time procedure designated as $StressLif{e}_{HCF}$ was developed. Through a combination of classic fatigue testing and non-destructive monitoring of the material response due to cyclic loading, a process-oriented fatigue life determination can be carried out. A total of two load increases and two constant amplitude tests are required for this procedure. By using data from non-destructive measurements, the parameters of the elastic approach according to Basquin and the plastic approach according to Manson–Coffin were determined and combined within the $StressLif{e}_{HCF}$ calculation. Furthermore, two additional variations of the $StressLif{e}_{HCF}$ method were developed in order to be able to accurately describe the S-N curve over a wider range. The main focus of this research was 20MnMoNi5-5 steel, which is a ferritic-bainitic steel (1.6310). This steel is widely used for spraylines in German nuclear power plants. In order to validate the findings, tests were also performed on an SAE 1045 steel (1.1191).

Tensile tests and fatigue tests on differently heat-treated low carbon (non- and low-alloy) steels were conducted and accompanied by non-destructive electrical resistometric (ER) and magnetic Barkhausen noise (MBN) measuring devices, in order to establish an improved short-time fatigue life estimation method according to StressLife. MaRePLife (Material Response Partitioning) is the hereby proposed method for calculating S–N curves in the HCF regime, based on the partitioning of material responses acquired during the above-mentioned mechanical tests. The rules were set to make use of the information gathered from pre-conducted tensile tests, which helps to determine the parameters of two load increase tests (LIT) and two constant amplitude tests (CAT). The results of the calculated S–N curves were satisfactory and could be verified by more separately conducted fatigue tests on specimens under different material conditions.

Materials used in nuclear power plants are exposed to cyclic loading, which is why the understanding of fatigue behaviour is of great importance. Because of high time investments and resulting increased costs, Lifetime Prediction Methods, which significantly reduce the amount of specimen, have already been developed. Within this paper, the Lifetime Prediction Method MiDAcLife_incr is presented, which enables a determination of a trend S‐N curve in the High‐Cycle‐Fatigue‐regime based on only one fatigue test and the combination of conventional fatigue testing with NDT‐related measurement techniques. The process‐orientated monitoring of the cyclic deformation behaviour provides the basis for the time‐ and cost‐effective provision of fatigue data. Compared with previous methods, the consideration of variable loading is an essential aspect of the research application. The test material is a 20MnMoNi5‐5 steel, the results of which are extended to include other steels for validation reasons.

Understanding the fatigue behaviour of metallic materials is highly important when it comes to a reliable assessment of material degradation as a result of dynamic loading. Because the provision of such data is associated with great testing effort leading to increased time and cost requirements in terms of conventional methods, accelerated lifetime prediction methods are becoming increasingly important. However, the reduced number of fatigue specimens and tests complicates statistical validations of the obtained results. In this contribution, combinatorial approaches are used to estimate both lifetime prediction bands and virtually-determined S-N curves with a reduced number of specimens, displaying the material-related scatter due to microstructural inhomogeneities. In addition, a variable energy dissipation factor based on cyclic deformation curves is presented, which enables evaluation of materials that exhibit more pronounced scatter, for instance cast materials. An in situ evaluation of the cyclic deformation curves is provided via integration of non-destructive testing methods into the testing rig. Unalloyed SAE 1045 steel, low-alloyed 20MnMoNi5-5 steel, and the cast material EN-GJS-1050-6 are investigated in this research, as these materials posses gradually increasing complexity regarding their respective microstructures.

This research provides a method for a reliable fatigue life estimation at high testing frequencies. The investigations are based on the lifetime prediction method StressLife_HCF considering test frequencies of 80 and 260 Hz for normalized SAE 1045 (C45E, 1.1191) steel. Therefore, load increase tests and constant amplitude tests were carried out using a resonant testing rig. To ensure a mechanism-oriented lifetime prediction, the material response to dynamic loading is monitored via temperature and electrical resistance measurements. Due to the higher energy input per time unit, when the test frequency is increased, the heat dissipation also increases. For this reason, a precise differentiation between frequency- and temperature-related effects for adequate fatigue assessment is challenging. To evaluate the temperature’s influence on electrical resistance, an electrical resistance-temperature hysteresis is measured, and the frequency influence is analyzed by considering cyclic deformation curves. In addition to an extension of the fatigue life due to an increased test frequency, the lifetime prediction method was validated for high frequencies. The generated S-N curves show a reliable agreement with the data points from conventional constant amplitude tests. In this context, the temperature correction of the electrical resistance proved to be an important input variable for a reliable lifetime prediction.