Primetals Technologies (Austria)

Abstract The variation of the O 2 content in the suction gas, in the range from 7 to 30 vol.%, during the iron ore sintering process, is investigated. Miniaturized laboratory-scale sintering experiments are carried out using an industry-like raw mixture to study the effects of O 2 variation on the sintering process with particular emphasis on the off-gas composition, specific sintering parameters and the sinter strength as well as the chemical composition of the sinter. After the ignition at the bed surface, the gas hood is placed on the sintering column, allowing a synthetic gas mixture to be drawn through the sinter bed until the burn-through point is reached. For additional interpretation of the experimental results, the theoretical coke combustion rate as a function of the oxygen partial pressure was calculated and plotted against the experimentally measured peak temperature in the sinter bed of the respective sinter series. An increasing O 2 content in the suction gas results in a faster flame front speed combined with a more gradual temperature rise of the heat wave and longer dwell time in the melt phase formation temperature range. Due to the more pronounced flame front, both sinter yield and strength increase, resulting in lower return rates. Below 12 vol.% O 2 , a sharp decrease in sinter yield and strength can be observed, probably due to the low extent of melt phase formation and the associated minor formation of silico ferrite of calcium and aluminum (SFCA). The carbon burnout as well as the calcination increases with increasing the O 2 content in the suction gas, resulting in higher levels of CO 2 in the off-gas, with more or less constant amounts of CO above 15 vol.% O 2 . The amounts of NO and SO 2 show a similar trend with a continuous increase with increasing O 2 supply, with the SO 2 breakthrough starting earlier and being released over a shorter period. The chemical analysis of the sinter indicates the highest Fe(II) values in the range of 12–21 vol.% O 2 in the suction gas.

Market requirements on steel products with the highest surface and internal quality demand stimulate a systematic control of the steel solidification behavior during continuous casting (CC). Computational process modeling is increasingly applied to optimize casting practices and calibrate the soft reduction to guarantee the required product quality. Here in this study, an overview of m2CAST as a “development platform” for the CC process is presented. This platform consists of a numerical heat‐transfer model, considers results of laboratory experiments in the calculations, for example, thermal analysis and nozzle measuring stand (NMS), and provides the option to use relevant process data. Two case studies on a continuous slab caster at voestalpine Stahl Linz GmbH are investigated. In doing so, thermal boundary conditions obtained by the NMS are implemented, and the simulation trials are validated with temperature measurements of the dragged thermocouple method installed during the casting process. The temperature distribution over the strand width is measured additionally with two pyrometers placed in the straightening zone. Excellent agreement between the calculated strand surface temperature and the measured temperature is obtained. Furthermore, the relevance of considering the roller‐bearing areas in defining the boundary conditions is presented to accurately predict the shape of the crater end.

Continuous casting (CC) is nowadays the world‐leading technology for steel production. The thin slab casting (TSC) is featured by a slab shape close to the final products and a high casting speed. The quality of the thin slabs strongly depends on the uniformity of the turbulent flow and the superheat distribution, defining the solid shell growth against a funnel‐shaped mold. In most studies, it is commonly assumed that the submerged entry nozzle (SEN) is properly arranged, and the melt inflow is symmetric. However, the misalignment or clogging of the nozzle can lead to an asymmetric flow pattern. Herein, the asymmetry is imposed via a partial SEN clogging: a) a local porous zone inside the nozzle reflects the presence of the clog material; b) the resistance of the clog is varied from low to high values. The solidification during TSC is modeled, including the effects of the turbulent flow. The variation of the flow pattern and the solidified shell thickness are studied for different permeability values of the SEN clogging. These effects are considered with and without the applied electromagnetic brake (EMBr) using an in‐house magnetohydrodynamics (MHD) and solidification solver developed within the open‐source package OpenFOAM.

A funnel-type mold is commonly used to provide necessary clearance for the submerged entry nozzle in the thin slab casting (TSC). The partially solidified shell is subjected to the mechanical deformations, which can lead to the defects formation and, as a results, to a breakout. Traditionally, the results of the flow simulation, performed by the finite volume method (FVM), are fed to the external package for the finite element analysis of stress and strain. A coupled model was assembled using “creeping solid” approach by blending the Norton-Hoff viscoplastic stress for the solidifying shell with the Newtonian viscous stress of the liquid melt. The FVM was used to combine both liquid and solid stress models within a single solver. The iterative procedure based on the improved both side diffusion method was introduced to treat the nonlinear relation between the viscoplastic stress and the strain rate. The modeled shell thickness was verified by previously published breakout measurements and the simulation results. Temperature distribution, obtained during the TSC simulation, dominantly corresponds to the viscoplastic range. Developed numerical approach is robust and has direct industrial application.

Abstract BackgroundThe evidence of social robots for people with dementia (PwD) living at home is unclear. The aim was to explore the effects of Coach Pepper (socially assistive humanoid robot system “AMIGO” combined with external tablet‐based training) versus an exclusively tablet‐based training on quality of life, motivation, cognition, mobility, care dependency, depression, and neuropsychiatric symptoms, as well as the user experience with Coach Pepper.MethodsThe study (2019‐2020) includes a randomized controlled trial with complementary interviews using content analysis. The intervention group (16 PwD) received Coach Pepper and the control group (16 PwD) an exclusively tablet‐based training for three weeks. Data were collected using standardized questionnaires (AES, MOCA, DEMQOL, PAS, TUG, GDS, NPI) and interviews.ResultsIn both groups, PwD were >80 years old and mainly female. The mild stage of Alzheimer's was predominant in both groups. The comparison of quality of life (DEMQOL questionnaire) between the groups showed a significantly greater increase in the Coach Pepper group (X̅: 5.48 vs. ‐0.31; med: 4 vs. 2 points, p = 0.0226). Furthermore, global quality of life increased significantly in the Coach Pepper group (X̅: 0.4 vs. ‐0.2; med: 1.0 vs. 0.0 points; p = 0.013). All other outcomes did not differ significantly. Main qualitative results: Attitude/feelings ‐ PwD reacted mainly positively to Pepper. The PwD were generally not afraid of Pepper and did not feel repulsed. They found Pepper nice/pleasant and funny. Communication, social contacts ‐ Pepper was received well and integrated as a family member. His presence was not disturbing, more an enrichment. PwD regarded Pepper as a friend, child and contact person. He promoted communication in PwD. The life of PwD “bloomed” and they bonded with Pepper, which caused feelings of sadness after Pepper moved out. Meaningful activities‐ music and dance activities stimulated PwD particularly positively.ConclusionCoach Pepper significantly increased the quality of life of the PwD in the robot group. As the additional qualitative results demonstrate, this increase can be attributed in particular to the promotion of communication and social contacts by Pepper. Further research should focus on the increase of Pepper’s communication skills and program content.

This work represents an extended abstract of a study presented at the PRES 2016 conference. Despite the fact that alternative processes such as Corex® and Finex® have already been established on industrial scale, the blast furnace route continues to be the most important process used to produce pig iron. Due to its importance, a variety of models of the blast furnace process have been developed in the past decades. In addition to this, a well-established analogue representation of blast furnace operation is given by the Rist operating diagram. The target of this work was to create a comprehensive blast furnace model in the process simulation platform of gPROMS ModelBuilder®, which enables the description of interdependencies between the main blast furnace process, raceway conditions as well as the overall thermodynamic process conditions within a single mathematical model. As an example of possible applications of the developed model, a detailed analysis of the model behaviour under varying coke substitution scenarios was carried out in order to evaluate their CO2 abatement potentials.

In order to achieve decarburization and manganese retention simultaneously, CO2 was introduced in the smelting process of high-Mn twinning-induced plasticity (TWIP) steel. The effect of CO2 and O2 mixed injection on the decarburization and manganese retention was carried out based on the thermodynamics calculation and experimental research. The calculation results showed that the evaporation loss of manganese decreased dramatically with increasing CO2 blowing proportion, from the value close to 38 kg/t at pure O2 blowing to the value close to 4.4 kg/t at 40 vol pct CO2 proportion. The oxidation loss of manganese decreased from 70.5 to 41.7 kg/t when the CO2 blowing proportion increased from 0 to 40 vol pct. Additionally, the obtained data of the present experiments indicated that the introduction of CO2 could significantly lower the manganese loss and improve decarburization efficiency. The decarburization and manganese retention could be achieved simultaneously by replacing the partial oxygen with CO2 in the injected gas. Moreover, increasing the flow rate of the CO2-O2 gas mixture and increasing the melt temperature would improve decarburization efficiency but deteriorate the retention of manganese in the meantime.

Robust classification strongly depends on the combination of properly chosen features and the classification algorithm. This paper investigates an autoencoder for feature fusion together with recurrent neural networks such as the Long Short-Term Memory neural networks (LSTMs) in different configurations applied to a dataset of a material transport process. As an important outcome the investigations show that the application of features acquired from the autoencoder bottleneck layer in combination with a bidirectional LSTM improve the classification algorithm significantly and require fewer features in comparison to standard machine learning algorithms.

The oxygen steelmaking process in a Linz-Donawitz (LD) converter is responsible for more than 70% of annual crude steel production. Optimization of the process control and numerical simulation of the LD converter are some of the current challenges in ferrous metallurgical research. Because of the process conditions and oxidation of impurities of the hot metal, a lot of chemical heat is generated. Therefore, steel scrap is charged as a coolant with the economical side aspect of its recycling. One of the more complex aspects is, among others, the dissolution and melting behaviour of the scrap in carbon-saturated hot metal. Heat and mass transfer act simultaneously, which has already been investigated by several researchers using different experimental approaches. The appearances at the interface between solid steel and liquid hot metal during diffusive scrap melting have been described theoretically but never investigated in detail. After an experimental investigation under natural and forced convective conditions, the samples were further investigated with optical microscopy and electron probe microanalysis (EPMA). A steep carbon concentration gradient in the liquid appeared, which started at an interface carbon concentration equal to the concentration on the solid side of the interface. Moreover, the boundary layer thickness moved towards zero, which symbolized that the boundary layer theory based on thermodynamic equilibrium was not valid. This fact was concluded through the prevailing dynamic conditions formed by natural and forced convection.