Numerical support of materials development and production

Numerical methods that support materials development and process optimization for the production of steel materials are increasingly used in order to optimize material properties and to reduce development times and resources in the steel works. Various methods are used to ensure a fast and economical development or optimization process.

Even in the early stages of materials development, thermodynamic-based calculations can be used to model and improve phase compositions, precipitation behavior and material properties. These calculations can provide information about the effect of the alloy elements used in order to create an optimum material design.

view larger image

Figure 1

For example, phase transformation and the dissolution and formation of precipitates can be modeled during hot rolling, as shown in Figure 1. In this way, the necessary re-heat temperature and time in the pusher-type furnace can be determined before hot rolling in order to largely dissolve the precipitates in the slab with minimum energy consumption.

Another example is cooling hot strip after rolling. The temperature distribution in the strip affects the transformation and precipitation processes and is essentially determined by the strip cooling and transformation processes.
In order to optimize temperature management, the cooling process on the cooling section and on the reel in the coil is modeled thermodynamically. Heat conduction plays a significant role, as do heat radiation, the heat transfer to the air and cooling water, and the latent heat that occurs during phase transition. The required physical properties of the material are derived from thermodynamic equilibrium calculations.
The time-temperature profile is calculated on the cooling section and during cooling in the wound coil as a function of the strip length, width and thickness. Using the numerical process simulation of the cooling section, for example, by calculating various cooling strategies, a uniform temperature distribution and thus a homogenous structure across the thickness of the strip can be achieved.
Figure 2 shows the numerically supported optimization of strip cooling after hot rolling a 18.9-mm thick tube. Before optimizing hot-strip cooling, an inhomogeneous temperature distribution across the strip thickness is detected at the start of the cooling section. Calculating the temperature profile for various strip cooling systems showed that a homogenization of the temperature differences across the strip thickness and a secure setting of the desired structure with sufficiently rapid cooling can be achieved via a reduced cooling output at the start of strip cooling.

view larger image

Figure 3

Depending on the coil temperature, phase transformations and precipitation can occur in the coil, even after coiling the hot strip. By coupling the process and material simulation, the temperature development and formation of precipitation in the coil can be modeled (Figure 3). As the temperature distribution in the coil is not uniform, significant differences in precipitation properties can also occur, which can lead to inhomogeneous technological material properties. With the help of numerical simulation, the temperature distribution of the coil can be optimized via specific cooling and the material properties thus improved.
 
Mathematical methods can also be used to optimize the annealing of cold-rolled strip.
Using the example of the annealing process before hot-dip galvanizing the cold strip, a suitable process analysis using statistical methods can be used to optimize the properties of the galvanized material. In addition, the processing speed can be increased, which leads to an increase in productivity and a reduction in the required energy input.
To optimize the annealing process, the vertical furnace of the hot-dip galvanizing line 2 at Salzgitter Flachstahl is examined. The optimum heating of the strip requires the setting of a suitable profile of the energy input in the individual zones of the radial radiation tube furnace (RTF), a section of the furnace of the hot-dip galvanizing line 2.
To optimize the annealing process with regard to material properties and reducing the energy requirement, the process analysis can be used to calculate the default values for the required volumes of natural gas in the individual zones in the RTF. The boundary conditions of the strip annealed thus far are used in the model. Accordingly, the previous mode of operation can be modeled with 90% certainty for almost all strip. The strip speed, thickness and temperature at the first measuring point in the furnace are the main factors determining the consumption of natural gas.
These calculation results can now be used as input values for a computer-aided optimization of the furnace operation. The aim is to calculate a heating profile depending on width and thickness. This has to ensure a given total output throughout the furnace, depending on the target temperature of the strip, which guarantees sufficient energy input in the strip.
Using statistical process analysis methods, the energy input in the furnace can thus be reduced without impairing the material properties.

In many areas of steel production, mathematical methods can be used to reduce development and optimization time and also to reduce the amount of resources used by production processes.