Research on Solid Shell Growth during Continuous Steel Casting

The continuous steel casting process must simultaneously meet the requirements for production performance, quality and safety against breakouts. Knowing the thickness of the solidified shell, particularly at the exit of the mould, is useful for the casting process control and breakout prevention. Shell thickness is difficult to measure during casting; in practice, it is predicted by indirect methods and models. But after undesired rupture of the shell and leakage of the liquid steel, it is possible to measure the shell thickness directly. This article is focused on the problem of the growth and measurement of the solid shell obtained after the breakout of a round block with a diameter of 410 mm. An original methodology was developed in which a surface mesh of points was created from the individual scanned parts of the block using a 3D laser scanner. Research has shown differences of up to 6 mm between the maximum and minimum shell thickness at the mould exit. A regression function of the average shell thickness on time was found. The results of the real shell growth were further used for the verification of the original numerical model of cooling and solidification of the round block.

Use of Neural Networks for Lifetime Analysis of Teeming Ladles

When describing the behaviour and modelling of real systems, which are characterized by considerable complexity, great difficulty, and often the impossibility of their formal mathematical description, and whose operational monitoring and measurement are difficult, conventional analytical-statistical models run into the limits of their use. The application of these models leads to necessary simplifications, which cause insufficient adequacy of the resulting mathematical description. In such cases, it is appropriate for modelling to use the methods brought by a new scientific discipline-artificial intelligence. Artificial intelligence provides very promising tools for describing and controlling complex systems. The method of neural networks was chosen for the analysis of the lifetime of the teeming ladle. Artificial neural networks are mathematical models that approximate non-linear functions of an arbitrary waveform. The advantage of neural networks is their ability to generalize the dependencies between individual quantities by learning the presented patterns. This property of a neural network is referred to as generalization. Their use is suitable for processing complex problems where the dependencies between individual quantities are not exactly known.

Corrosive Effect of Wood Ash Produced by Biomass Combustion on Refractory Materials in a Binary Al-Si System

In terms of its chemical composition, biomass is a very complex type of fuel. Its combustion leads to the formation of materials such as alkaline ash and gases, and there is evidence of the corrosive effect this process has on refractory linings, thus shortening the service life of the combustion unit. This frequently encountered process is known as "alkaline oxidative bursting". Corrosion is very complex, and it has not been completely described yet. Alkaline corrosion is the most common cause of furnace-lining degradation in aggregates that burn biomass. This article deals with an experiment investigating the corrosion resistance of 2 types of refractory materials in the Al₂O₃-SiO₂ binary system, for the following compositions: I. (53 wt.% SiO₂/42 wt.% Al₂O₃) and II. (28 wt.% SiO₂/46 wt.% Al₂O₃/12 wt.% SiC). These were exposed to seven types of ash obtained from one biomass combustion company in the Czech Republic. The chemical composition of the ash is a good indicator of the problematic nature of a type of biomass. The ashes were analyzed by X-ray diffraction and X-ray fluorescence. Analysis confirmed that ash composition varies. The experiment also included the calculation of the so-called "slagging/fouling index" (I/C, TA, Sr, B/A, Fu, etc.), which can be used to estimate the probability of slag formation in combustion units. The corrosive effect on refractory materials was evaluated according to the norm ČSN P CEN/TS 15418, and a static corrosion test was used to investigate sample corrosion.

Experience with application of reagent to heat transfer surfaces of combustion device

The formation of deposits on heat exchange surfaces of combustion equipment causes a decrease in heat exchange, a decrease in power, and consequently deterioration in the economic balance of combustion equipment. The technology of French company A. I. T. DRIVEX has been developing and being applied in practice for many decades. Preventive technology is used as a mean reagent periodically injected during operation into the combustion chamber. Part of the application is always pre-prepared project resolving the location of the injection nozzles into the combustion chamber on the flue gas path. The article describes the experimental usage of reagent GEPERSUITE 2200 at the Sermaize refinery in France. The aim of the test is to evaluate the benefits and advantages of applied technology in the boiler refinery in full operation. The results clearly demonstrate that using the reagent GEPERSUITE 2200 is advantageous in terms of economic and technical properties.