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Forming complex parts out of high and ultra-high strength aluminium alloys has proved to be more challenging in comparison to the currently used deep drawing steels. Nevertheless, aluminium alloys show a limited formability in contrast with, for example, deep drawing steels. Novel processes like Warm-forming, W-Temper or Hotforming, offer the potential to produce light and highly integrated one-piece components from such aluminium alloys at elevated temperatures. When considering aluminium alloys of the 7000 group, which can reach strength values (UTS) of about 600 MPa, crash components such as side impact bars would offer a suitable field of application.
Forming at elevated temperatures, in particular with the Hotforming process, offers high potential in the production of complex structural components on the one hand and in the use of existing press hardening equipment on the other. To date, the material behaviour of aluminium alloys in the 7000 group, applied in such processes and in the later final state after forming, is not sufficiently known.
Therefore, in this study, systematic investigations on the formability and the final strength during and after forming at elevated temperature of the EN AW-7075 aluminium wrought alloy from different suppliers are conducted. In general, material- and damage/ failure models were created and implemented into simulation in order to make predictions. Characterisation of the plastic material properties on the basis of various tensile specimens as shear-, notched-, tensile- and Erichsen tests are carried out to adapt the complex material- and failure models such as Barlat YLD2000 and GISSMO to the experimental values using a parameter optimisation. These were made for the material conditions during forming, i.e. after solution heat treatment, the final condition after artificial ageing at 180°C for 20 minutes, which corresponds to the cathodic dip coating, and the T6 condition, which is the highest strength condition.
To evaluate a suitable friction coefficient for high temperature forming processes, anti-friction agents are screened, and the potential applicability evaluated by strip-drawing tests. Thereby, using an analytical relationship, friction coefficients are determined at room temperature and 180°C, which are used as corresponding friction model for the finite element forming simulation.
Crash simulations using the nonlinear finite element method (FEM) of side impact protection beams are used to demonstrate the weight saving potential of high and ultra-high strength aluminium alloys compared to a beam made of press hardened steel. A weight saving of about 20 % could be achieved with the same crash performance. This can be significantly increased to around 30 % - 40 % by using local reinforcements such as CFRP or GFRP (carbon/ glass fibre reinforced plastic) patch. For this reason, a novel process was developed which is based on the conventional Hotforming process with an integrated thermal direct joining step called “Extended Hotforming”.
Subsequently, a heatable forming tool for the production of a serial like sheet metal side impact beam was developed to validate the finite element simulation and to demonstrate the potential of the forming processes at elevated temperatures for aluminium sheet metal components.
The surface topography of biodegradable polymer foils is modified by mechanical imprinting on a submillimeter length scale. The created patterns strongly influence the wetting behavior and allow the preparation of hydrophobic surfaces with controlled solid-liquid interaction. A detailed analysis of anisotropic surface patterns reveals that the observed effect arises from a combination of topographical and compositional changes that are introduced to the surface. As a main result it is found that an individual combination of material and structure is required for the production of water-repellent biopolymer foils that are highly attractive for packaging applications.
Based on a data-driven approach, a computer-assisted workflow for the quantitative analysis of optical Kerr microscopy images of sintered FeNdB-type permanent magnets was developed. By analyzing the domain patterns visible in the Kerr image with data-driven approaches such as traditional machine learning and advanced deep learning, we can quantify grain orientation and size with a better trade-off between accuracy and higher throughput than electron backscatter diffraction (EBSD). The key distinction between traditional machine learning and advanced deep learning lies in feature extraction. Traditional methods require manual, user-dependent feature extraction from input data, while advanced deep learning achieves this automatically. The predictions from the trained models were compared to the measurements from EBSD for performance evaluation. The proposed data-driven model is trained on the dataset created from the correlative microscopy technique, which requires the images of grains extracted from the Kerr microscopy and corresponding EBSD grain orientation data (Euler angles). The fine-tuned deep learning model shows better generalization ability than the traditional machine learning models trained on the manually extracted features and resulted in a mean absolute error of less than 5° for grain orientation of the anisotropic magnet samples when evaluated against the measured EBSD values. The developed approach has reduced the measurement effort for grain orientation by 5 times and have sufficient accuracy when compared to the EBSD.
Direct Digital Manufacturing - The Role of Cost Accounting for Online Hubs to Access Industry 4.0
(2021)
Direct digital manufacturing – the role of cost accounting for online hubs to access industry 4.0
(2021)
Highlighting Thermal Post-Treatment for Improving Long-Term Media-Tightness of Polymer-Metal Hybrids
(2021)
Integrated laser based pre‐tempering at laser welding of AISI 1045 steel by using 3D‐scanner optics
(2021)
Laser melting manufacturing of large elements of lunar regolith simulant for paving on the Moon
(2023)
The next steps for the expansion of the human presence in the solar system will be taken on the Moon. However, due to the low lunar gravity, the suspended dust generated when lunar rovers move across the lunar soil is a significant risk for lunar missions as it can affect the systems of the exploration vehicles. One solution to mitigate this problem is the construction of roads and landing pads on the Moon. In addition, to increase the sustainability of future lunar missions, in-situ resource utilization (ISRU) techniques must be developed. In this paper, the use of concentrated light for paving on the Moon by melting the lunar regolith is investigated. As a substitute of the concentrated sunlight, a high-power CO2 laser is used in the experiments. With this set-up, a maximum laser spot diameter of 100 mm can be achieved, which translates in high thicknesses of the consolidated layers. Furthermore, the lunar regolith simulant EAC-1A is used as a substitute of the actual lunar soil. At the end of the study, large samples (approximately 250 × 250 mm) with interlocking capabilities were fabricated by melting the lunar simulant with the laser directly on the powder bed. Large areas of lunar soil can be covered with these samples and serve as roads and landing pads, decreasing the propagation of lunar dust. These manufactured samples were analysed regarding their mineralogical composition, internal structure and mechanical properties.
Future lunar exploration will be based on in-situ resource utilization (ISRU) techniques. The most abundant raw material on the Moon is lunar regolith, which, however, is very scarce on Earth, making the study of simulants a necessity. The objective of this study is to characterize and investigate the sintering behavior of EAC-1A lunar regolith simulant. The characterization of the simulant included the determination of the phase assemblage, characteristic temperatures determination and water content analysis. The results are discussed in the context of sintering experiments of EAC-1A simulant, which showed that the material can be sintered to a relative density close to 90%, but only within a very narrow range of temperatures (20–30 °C). Sintering experiments were performed for sieved and unsieved, as well as for dried and non-dried specimens of EAC-1A. In addition, an analysis of the densification and mechanical properties of the sintered specimens was done. The sintering experiments at different temperatures showed that the finest fraction of sieved simulant can reach a higher maximum sintering temperature, and consequently a higher densification and biaxial strength. The non-dried powder exhibited higher densification and biaxial strength after sintering compared to the dried specimen. This difference was explained with a higher green density of the non-dried powder during pressing, rather than due to an actual influence on the sintering mechanism. Nevertheless, drying the powder prior to sintering is important to avoid the overestimation of the strength of specimens to be fabricated on the Moon.
In this study, we investigate the use of artificial neural networks as a potentially efficient method to determine the rate capability of electrodes for lithium-ion batteries with different porosities. The performance of a lithium-ion battery is, to a large extent, determined by the microstructure (i.e., layer thickness and porosity) of its electrodes. Tailoring the microstructure to a specific application is a crucial process in battery development. However, unravelling the complex correlations between microstructure and rate performance using either experiments or simulations is time-consuming and costly. Our approach provides a swift method for predicting the rate capability of battery electrodes by using machine learning on microstructural images of electrode cross-sections. We train multiple models in order to predict the specific capacity based on the batteries’ microstructure and investigate the decisive parts of the microstructure through the use of explainable artificial intelligence (XAI) methods. Our study shows that even comparably small neural network architectures are capable of providing state-of-the-art prediction results. In addition to this, our XAI studies demonstrate that the models are using understandable human features while ignoring present artefacts.
The Dimensional Accuracy of Thin-Walled Parts Manufactured by Laser-Powder Bed Fusion Process
(2020)
Soft magnetic Fe-Al alloys have been a subject of research in the past. However, they never saw the same reception in technical applications as the Fe-Si or Fe-Ni alloys, which is, to some extent, due to a low ductility level and difficulties in manufacturing. Additive manufacturing (AM) technology could be a way to avoid issues in conventional manufacturing and produce soft magnetic components from these alloys, as has already been shown with similarly brittle Fe-Si alloys. While AM has already been applied to certain Fe-Al alloys, no magnetic properties of AM Fe-Al alloys have been reported in the literature so far. Therefore, in this work, a Fe-12Al alloy was additively manufactured through laser powder bed fusion (L-PBF) and characterized regarding its microstructure and magnetic properties. A comparison was made with the materials produced by casting and rolling, prepared from melts with an identical chemical composition. In order to improve the magnetic properties, a heat treatment at a higher temperature (1300 °C) than typically applied for conventionally manufactured materials (850–1150 °C) is proposed for the AM material. The specially heat-treated AM material reached values (HC: 11.3 A/m; µmax: 13.1 × 103) that were close to the heat-treated cast material (HC: 12.4 A/m; µmax: 20.3 × 103). While the DC magnetic values of hot- and cold-rolled materials (HC: 3.2 to 4.1 A/m; µmax: 36.6 to 40.4 × 103) were not met, the AM material actually showed fewer losses than the rolled material under AC conditions. One explanation for this effect can be domain refinement effects. This study shows that it is possible to additively manufacture Fe-Al alloys with good soft magnetic behavior. With optimized manufacturing and post-processing, further improvements of the magnetic properties of AM L-PBF Fe-12Al may still be possible.