Application of evolutionary rietveld method based XRD phase analysis and a self-configuring genetic algorithm to the inspection of electrolyte composition in aluminum electrolysis baths

The technological inspection of the electrolyte composition in aluminum production is performed using calibration X-ray quantitative phase analysis (QPA). For this purpose, the use of QPA by the Rietveld method, which does not require the creation of multiphase reference samples and is able to take into account the actual structure of the phases in the samples, could be promising. However, its limitations are in its low automation and in the problem of setting the correct initial values of profile and structural parameters. A possible solution to this problem is the application of the genetic algorithm we proposed earlier for finding suitable initial parameter values individually for each sample. However, the genetic algorithm also needs tuning. A self-configuring genetic algorithm that does not require tuning and provides a fully automatic analysis of the electrolyte composition by the Rietveld method was proposed, and successful testing results were presented. © 2018 by the authors. Licensee MDPI, Basel, Switzerland

Rietveld Refinement in the Characterization of Crystalline Materials

This Special Issue serves as a crystallographic forum covering various aspects of material science that have in common the use of the powerful Rietveld method in the analysis of the powder XRD patterns of investigated compounds

Process Modeling in Pyrometallurgical Engineering

The Special Issue presents almost 40 papers on recent research in modeling of pyrometallurgical systems, including physical models, first-principles models, detailed CFD and DEM models as well as statistical models or models based on machine learning. The models cover the whole production chain from raw materials processing through the reduction and conversion unit processes to ladle treatment, casting, and rolling. The papers illustrate how models can be used for shedding light on complex and inaccessible processes characterized by high temperatures and hostile environment, in order to improve process performance, product quality, or yield and to reduce the requirements of virgin raw materials and to suppress harmful emissions

Material Transfer Buildup on PVD Coated Work Rolls during Hot Rolling of an Al Alloy

This study examines material transfer and adhesion from Al-Mg alloy samples to various PVD coatings deposited on AISI M2 steel rolls during hot rolling. It explores to examine if these PVD coatings can aid in extending the work roll life by either mitigating against material transfer or aiding in the early development of the roll coatings. Scanning electron microscopy (SEM) and focus ion beam (FIB) microscopy were used to investigate material transfer and adhesion to the surfaces of the work rolls. Aluminum and magnesium transfers were observed on all work rolls\u27 surfaces from the 1st hot rolling pass. A two-way material transfer mechanism between the work roll and the rolled aluminum alloy surfaces was confirmed to determine the amount of material transfer on the work roll surfaces. The lubrication flow rate was reduced to examine the lubrication’s influence on the Al/Mg adhesion mitigation behavior of Cr and TiCN PVD coatings during hot rolling. The emulsion was identified as playing a significant role in the Al/Mg transfer and buildup of roll coatings on the work roll surfaces. Under both high and low lubrication conditions during hot rolling no damage was observed on the work roll surfaces which indicated that the PVD coatings were effective at extending the work roll life, although they were not able to totally mitigate against Al/Mg transfer and buildup on the work roll surfaces

Metallurgical Process Simulation and Optimization

Metallurgy involves the art and science of extracting metals from their ores and modifying the metals for use. With thousands of years of development, many interdisciplinary technologies have been introduced into this traditional and large-scale industry. In modern metallurgical practices, modelling and simulation are widely used to provide solutions in the areas of design, control, optimization, and visualization, and are becoming increasingly significant in the progress of digital transformation and intelligent metallurgy. This Special Issue (SI), entitled “Metallurgical Process Simulation and Optimization”, has been organized as a platform to present the recent advances in the field of modelling and optimization of metallurgical processes, which covers the processes of electric/oxygen steel-making, secondary metallurgy, (continuous) casting, and processing. Eighteen articles have been included that concern various aspects of the topic