Dendrite growth direction measurements : understanding the solute advancement in continuous casting of steel

Maintaining competitiveness in steel manufacturing requires improving process efficiency and production volume whilst enhancing product quality and performance. This is particularly challenging for producing value-added advanced steel grades such as advanced high strength steels and electrical steels. These grades due to higher weight percentage of alloying elements cause difficulties in various stages of upstream and downstream processing, and this includes continuous casting, wherein high solute levels are critical towards macro-segregation. Interface growth direction in systems with more than one component is dictated by the solute profile ahead of the moving solidification front. Understanding the profile of growth direction with casting process parameters during the progress of casting will provide an important perspective towards reducing the macro-segregation in the cast product. In the present study, two steel slab samples from conventional slab caster under the influence of electromagnetic brake (EMBR) at Tata Steel in IJmuiden (The Netherlands) have been investigated for dendrite deflection measurements. The samples showed a transition zone where a change in the deflection behavior occurs. Also, the magnitude of the deflection angle decreases away from the slab surface. Correlating these experimental data with modeled fluid flow profile will help in improving the understanding of the dynamic nature of the solute advancement so that the casting parameters can be optimized to improve product quality

Early Child Development in Social Context: A Chartbook

Reviews more than 30 key indicators of health and development for children up to age 6, as well as social factors in families and communities that affect these outcomes. Offers practical suggestions for health practitioners and parents

Thermodynamics of the iron-nitrogen system with vacancies. From first principles to applications

Density Functional Theory (DFT) and Atomistic Kinetic Monte Carlo is employed in this work to assess the thermodynamic behaviour of the α (BCC) and γ (FCC) allotropes in the iron-nitrogen system. The calculated nitrogen solubility at unit nitrogen activity from (250 < T < 1538°C) is found to be significantly underestimated, beyond the uncertainty range of the calculation, in both phases. The boundary of the α-γ phase change as featured in Lehrer diagrams is calculated within the nitriding potential (0.001 < r_N < 10) and temperature (300 < T < 900°C) ranges. The boundary shows good agreement with experimental data, but the calculated α region is consistently smaller than the data suggests. Motivated by the existence of grain boundaries and other common defects which cause far more unoccupied volume within iron than is expected in idealised lattice structures, the effect of excess vacancy concentrations in varying ranges between 10^{−12} < c_v < 10 at.% on nitrogen solubility and the α-γ phase change is quantified. It is shown how discrepancies between the theoretical ideal crystal and experimental data can be "corrected" by excess vacancies to model the non-ideality of iron lattices in reality, and evidence is given for the validity of this correction. Results are presented in an applied context, allowing opportunities for experimental verification

A computational study on the reduction behavior of iron ore carbon composite pellets in both single and multi-layer bed rotary hearth furnace

A phenomenological model for the reduction of iron ore/carbon composite pellets in a multi-layer bed rotary hearth furnace has been developed. A single pellet model has been scaled up to a multi-pellet layer version in a computationally efficient way. The multi-layer pellet bed has been conceived as single column of identical pellets in a rectangular enclosure, assuming symmetry of the pellet bed in horizontal direction. The column walls are considered opaque with respect to heat transfer but allow heat radiation to reach the pellet surface through multiple reflections from the wall. The time-temperature-transformation and time-temperature-chemical heat absorption contours are presented to provide a better understanding of the reduction process. Finally, the net heat flux and carbon monoxide generation, emerging from the multi-layer bed system has been generated, which may be used as source and sink terms for CFD simulations in the free board of the RHF

Numerical modelling of thermal quantities for improving remote laser welding process capability space with consideration to beam oscillation

This research aims to explore the impact of welding process parameters and beam oscillation on weld thermal cycle during laser welding. A three-dimensional heat transfer model is developed to simulate the welding process, based on finite element method. The results obtained from the model pertaining to thermal cycle and weld morphology are in good agreement with experimental results found in the literature. The developed heat transfer model can quantify the effect of welding process parameters (i.e. heat source power, welding speed, radius of oscillation, and frequecy of oscillation) on the intermediate performance indicators (IPIs) (i.e. peak temperature, heat-affected zone (HAZ) volume, and cooling rate). Parametric contour maps for peak temperature, HAZ volume, and cooling rate are developed for the estimation of the process capability space. An integrated approach for rapid process assessment, and process capability space refinement, based on IPIs is proposed. The process capability space will guide the identification of the initial welding process parameters window and helps in reducing the number of experiments required by refining the process parameters based on the interactions with the IPIs. Among the IPIs, the peak temperature indicates the mode of welding while the HAZ volume and cooling rate represent weld quality. The regression relationship between the welding process parameters and the IPIs is established for quick estimation of IPIs to replace time-consuming numerical simulations. The application of beam oscillation widens the process capability space, making the process parameter selection more flexible due to the increase in distance from the tolerance boundaries

Uncertainty quantification of time-dependent quantities in a system with adjustable level of smoothness

We summarise the results of a computational study involved with Uncertainty Quantification (UQ) in a benchmark turbulent burner flame simulation. UQ analysis of this simulation enables one to analyse the convergence performance of one of the most widely-used uncertainty propagation techniques, Polynomial Chaos Expansion (PCE) at varying levels of system smoothness. This is possible because in the burner flame simulations, the smoothness of the time-dependent temperature, which is the study’s Quantity of Interest (QoI) is found to evolve with the flame development state. This analysis is deemed important as it is known that PCE cannot construct an accurate data-fitted surrogate model for non-smooth QoIs and thus estimate statistically convergent QoIs of a model subject to uncertainties. While this restriction is known and gets accounted for, there is no understanding whether there is a quantifiable scaling relationship between the PCE’s convergence metrics and the level of QoI’s smoothness. It is found that the level of QoI-smoothness can be quantified by its standard deviation allowing to observe the effect of QoI’s level of smoothness on the PCE’s convergence performance. It is found that for our flow scenario, there exists a power-law relationship between a comparative parameter, defined to measure the PCE’s convergence performance relative to Monte Carlo sampling, and the QoI’s standard deviation, which allows us to make a more weighted decision on the choice of the uncertainty propagation technique

Numerical simulation of transport phenomena and its effect on the weld profile and solute distribution during laser welding of dissimilar aluminium alloys with and without beam oscillation

Remote Laser Welding (RLW) of Aluminium alloys has significant importance in lightweight manufacturing to decrease the weight of the body in white. It is critical to understand the physical process of transport phenomena during welding which is highly related to the mechanical performance of the joints. To investigate the underlying physics during welding and to understand the influence of beam oscillation on heat transfer, fluid flow and material mixing a transient three-dimensional Finite Element (FE) based Multiphysics model has been developed and validated from the experiments. The effect of welding speed, oscillation amplitude and oscillation frequency on the fusion zone dimensions, flow profile, vorticity profile, cooling rate and thermal gradient during the butt welding of Al-5754 to Al-6005, with sinusoidal beam oscillation, is analysed. It was found that one additional vortex is formed during beam oscillation welding due to the churning action of the oscillating beam. With the increase in oscillation amplitude, welds become wider and the depth of penetration decreases. An increase in oscillation frequency leads to an increase in the flow rate of the molten metal suggesting that the beam oscillation introduces a churning action that leads to an increase in mixing. It was highlighted that the material mixing depends on both diffusion and convection

A multiscale-based approach to understand dendrite deflection in continuously cast steel slab samples

Dendrite bending angle measurements were conducted along two different directions on four steel slab samples collected from a conventional caster. The primary dendrites growing at the slab surface showed a transition in their growth direction as the distance from the surface increased. Numerical fluid flow simulation showed changes in the flow directions that might have caused the change in the growth direction. The bending angle measurements were also correlated with the casting process parameters. Thereafter, a multiscale approach was adopted to predict the dendrite deflection angles by correlating the macro-scale flow profile with the micro-scale bending angle formulation and subsequently corroborated with the industrial scale measurements

Effect of nanoparticle size on the near-surface pH-distribution in aqueous and carbonate buffered solutions

An analytical solution for the effect of particle size on the current density and near-surface ion distribution around spherical nanoparticles is presented in this work. With the long-term aim to support predictions on corrosion reactions in the human body, the spherical diffusion equation was solved for a set of differential equations and algebraic relations for pure unbuffered and carbonate buffered solutions. It was shown that current densities increase significantly with a decrease in particle size, suggesting this will lead to an increased dissolution rate. Near-surface ion distributions show the formation of a steep pH-gradient near the nanoparticle surface (\u3c6 μm) which is further enhanced in the presence of a carbonate buffer (\u3c2 μm). Results suggest that nanoparticles in pure electrolytes not only dissolve faster than bigger particles but that local pH-gradients may influence interactions with the biological environment, which should be considered in future studies