## 1 Introduction
Investigations by [PERSON], [PERSON], and [PERSON] showed a frequency dependence for different stress ratios concerning the HCF fatigue behavior of Ti-6 Al-4V specimens [14]. [PERSON] et al. [15] introduced a new possibility to assess whether a test frequency effect may occur for high-temperature tests by defining a parameter that takes the homologous temperature and material strength into account. [PERSON]'s research [16] in the 1960s focused on the influence of plastic deformation energy per cycle and its crucial role in the related damage evolution in material. [PERSON] explored how cyclic loading leads to energy accumulation, contributing to material fatigue over time, and introduced cyclic plastic strain energy as a critical metric for understanding fatigue behavior. Based on his research, damage indicators were defined due to the heat generation derived from the dissipative energy associated with microstructural deformation mechanisms. These indicators can be derived from direct and indirect temperature measurements and are used to estimate the fatigue strength of metallic materials [17; 18; 19; 20; 21; 22]. Building on [PERSON]'s foundational work on cyclic plastic strain energy in fatigue behavior, it is also essential to consider frequency-dependent self-heating in the context of fatigue testing at higher frequencies. At elevated test frequencies, the rapid succession of plastic deformation cycles leads to continuous heat accumulation in the material, as the limited time available for heat dissipation between load cycles restricts heat dissipation [23]. In order to reduce the number of specimens and the required time to provide S-N curves while achieving precise agreement between the calculated and experimental results, various lifetime prediction methods (LPM) [24; 25; 26; 27; 28; 29; 30; 31; 32] have been developed recently. The potential of non-destructive testing (NDT), the digitalization of measurement technology, and signal processing are combined in these methods in order to achieve an increased level of information regarding fatigue behavior. Since the generation of S-N curves requires more than 20 tests according to the standard DIN 50100 [33], the previously mentioned methods can demonstrably reduce the associated effort. For instance, high-resolution IR cameras allow microstructure-resolved damage detection, which can be used as a basis for a direct correlation with the degradation evolution of the materials [34; 35]. Within the presented research, the frequency dependence of the fatigue life is integrated into a lifetime prediction method based on StressLife, which has been developed in previous research [24; 25]. Therefore, this method is used for the first time regarding the increased test frequencies of 80 Hz and 260 Hz. Apart from temperature-based methods, electrical resistance measurement methods are also well suited for in situ measurements in fatigue tests, even on complex components and structures. Changes in the electrical resistance can directly be correlated with microstructural degradations [36]. This method is appropriate for in situ measurements as well as for determinations in load-free intervals. In addition to the geometry, the electrical resistance depends on the specific electrical resistance, which is made up of temperature-independent and temperature-dependent portions, according to [PERSON] [37], as well as changes during plastic deformation due to variations in defect density [38; 39; 40]. Due to the reduction of the effective specimen cross-section, the electrical resistance exhibits a very distinctive sensitivity concerning crack initiation and propagation. As a consequence of the high self-heating of the specimens caused by the increased test frequency [41], there is a temperature effect on the specimens in addition to a frequency effect. In order to increase the sensitivity with regard to microstructural changes, the temperature-dependent portion of the electrical resistance is minimized within the framework of this research.