Konferenzbeiträge

The use of high-strength structural steels brings great advantages in constructions regarding material requirements, weight reduction and productivity. Different steel grades within the S960 range are commercially available but not yet represented in Eurocode 3. The weldability of these steels is limited to smaller process windows to ensure the high material properties. In contrast to steels with moderate strength, there is a considerable risk of softening in the heat-affected zone causing a strength reduction of the connection. By now, the current EN 1993-1-12 only extends the design rules to cover steel grades up to S700. Therefore, the potential of these high-strength steels cannot be used to its full extent in structural engineering. This study, made within a steel application research project (FOSTA P 1507), deals with the weldability and load-carrying capacity of butt and fillet welded joints of S960QL and S960MC produced by gas-shielded metal arc welding. The influence of different bevel geometry, filler metal, and plate thicknesses was investigated. To extend the design rules up to S960, a need of an amendment was found for some combinations.

High-strength structural steels are beneficial in terms of the sustainability of constructions due to the possible reduction of weight and overall material needs. Nevertheless, high-strength steels have a smaller processing parameter range in regarding the specific heat input and resulting cooling rate. Especially the cooling time t8/5 characterizing the time span to cool down from 800 to 500 ˚C is an important indicator. Single layer butt-welded gas metal arc welding (GMAW) connections of 3 mm plates between normal strength (S355J2+N, S460MC) and high-strength steels (S700MC) as well as matched connections (S460MC, S700MC) are carried out. Hereby, the influence of the energy input, melting rate, joint preparation, filler metal (matching and undermatching) and backing methods are observed. Spatially resolved IR-thermal observation shows variations within the welds of up to 50 % in the cooling time t8/5 depending on those parameters. These fluctuations lead to significant changes of the microstructure within the melting and heat-affected zone. UCI hardness mappings show the softening and microstructural change within these zones. Those soft zones can be the region of failure for butt welded connections as shown by transverse tensile tests with spatially resolved optical strain measurements. The results obtained can be used to define more precise welding procedures of these types of connections and also are used to develop design rules for mixed connections made of normal strength and high-strength steel.

The calculation of the temperature of high-voltage transmission lines is usually done by the commercially used standard models, the CIGRE Standard No. 601 and the IEEE Standard No. 738. These turn out to be prone to errors in application. Based on data analysis, new models based on machine learning techniques and their combination with physics-based models, called physics-guided machine learning techniques, were developed and compared with the results of the established physical models and measurement results. The improved models achieve a reduction of the mean absolute estimation error as well as a significant reduction of the values that deviate more than 5 K from the measured conductor temperature. Also, the mean underestimation of the conductor temperature was changed into an applicationtechnically unproblematic overestimation by the transition from the best standard to the best data-scientific model. The optimization of the models could be achieved by eliminating the incorrect determination of the physical parameters, a compensation of the conservative estimation of the physical effects as well as the consideration of the neglected thermal components of the heat balance. The investigations are based on measured data of the conductor temperature and electrical quantities from the grid area of 50Hertz Transmission GmbH.

This paper investigates the potential of airborne sound analysis in the human hearing range for automatic defect classification in the arc welding process. We propose a novel sensor setup using microphones and perform several recording sessions under different process conditions. The proposed quality monitoring method using convolutional neural networks achieves 80.5% accuracy in detecting deviations in the arc welding process. This confirms the suitability of airborne analysis and leaves room for improvement in future work.

This work describes the use of a compact fiber-interferometric sensor for velocity measurements for the Kibble balance method. Our fiber-interferometric sensor was compared within a Planck-balance setup with a commercial reference interferometer. Results show that the fiber-interferometric sensor is capable of high accuracy velocity measurement comparable with the reference interferometer. High performance and compactness of the sensor head allow it to be integrated into small-size systems, where the use of the conventional interferometer systems is limited or not possible.