In order to achieve realistic simulations of the chip formation, high quality input data regarding the flow stress and damage behavior of the materials are required. The split Hopkinson pressure bar (SHPB) test setup for the characterization of highly dynamic material properties offers a suitable method for generating high strain rates, similar to those in the chip formation zone. However, the strain measurement in SHPB is usually performed by means of strain gauges. This leads to an unreliable evaluation of strain rate and flow stress/shear flow stress in the case of an inhomogeneous material deformation, since this method presents the total strain whilst excluding local deformations. Inhomogeneous deformations are induced deliberately in special shear specimens, as they are also observed in the investigated cylindrical specimens. The present work deals with this issue by providing two additional measurement techniques, which are applied in SHPB tests for cylindrical specimens made of AISI 1045 and Ti6Al4V. To enable a local strain resolution, digital image correlation (DIC) is applied to high-speed images of the deformation process. In order to allow for the detection of shear bands in the specimens, a deep-learning-based approach is presented. The two measurement methods (strain gauges and DIC) are compared and discussed. In particular, the findings regarding the inhomogeneous deformation of Ti6Al4V allow for future improvements in the result quality of SHPB tests. The presented algorithm shows promising predictions for shear band detection and creates the basis for an automated evaluation of shear sample results, as well as an AI-based pre-selection of frames for the DIC evaluation of SHPB tests.

Due to their lightweight potential, the use of fiber-reinforced polymers is the current standard for many technical fields of application. Especially, the automotive and aerospace sectors are to be emphasized. This entails a sophisticated knowledge regarding the material properties, since the safety standards applied in these fields are of high importance. To ensure the safety of the components, a detailed mechanical material characterization is indispensable. The aim of this work was to investigate different influencing factors on the fatigue behavior of carbon fiber-reinforced polyurethane, which is to be certified for aviation applications. Tensile tests provided a basic understanding of the material properties, which appeared to be affected by the specimen width, varied from 3 to 25 mm, by up to 30%. Subsequently, the influence of the cutting direction was investigated in the course of the fatigue tests. Thus, the fatigue strength of longitudinally cut specimens was found to be higher than that of transversely cut specimens by 6%. By means of specific measurement technologies, the material responses were associated with crack initiation and propagation during the fatigue lifetime. The material properties, such as the thermoelastic effect, could be examined during the fatigue tests. Furthermore, turning points in the courses of the characteristic values of the material and correlations with local phenomena were identified.

The sustainable and fast-growing natural material bamboo accommodates the potential for partially substituting energy-intensive materials in specific technical applications (e.g., in the building industry), thus playing a significant role in bringing about a turning point in reducing the disconcerting effects of global warming and climate change. Beyond the mechanical properties required for the intended applications and rapid growth, the plant exhibits a notable ability of CO ₂ storage and eco-restoration. Bamboo is available in many different species in large parts of the world, growing under different climate conditions. With each species possessing its own unique characteristics, the Phyllostachys edulis (Moso) from the Asian region and the Guadua angustifolia (Guadua) from South America were contrasted as two of the best-known and most extensively researched species. The following investigations were conducted in accordance with normative standard ISO 22157 that has been previously established. Material responses are typically recorded using displacement sensors or strain gauges, which are spatially limited to the measurement zone. Because bamboo is a natural material with locally varying properties, this spatial limitation can lead to inaccuracies by failing to capture the actual material response during testing. Digital image correlation (DIC) is therefore employed, as it enables the observation of larger specimen areas and offers flexibility in subsequent data analysis. In addition, the area-based and visually interpretable evaluation makes it possible to assess whether loads are transferred uniformly or whether naturally occurring defects cause an uneven stress distribution, as discussed later in this paper. The method also serves to verify the intended load introduction into the bamboo culm and to identify, and thus exclude, local failure caused by improper loading. The mechanical test results confirmed the excellent mechanical properties of bamboo when loaded parallel to the fiber direction, as high strength values were observed particularly in compression and bending tests in this direction. While Guadua exhibited slightly higher compressive strength, Moso showed overall higher strengths in transverse tensile and bending tests. Generally, a marked reduction in strength was observed when comparing tensile tests perpendicular to the grain.