A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem

A new data-driven reference vector-guided evolutionary algorithm has been successfully implemented to construct surrogate models for various objectives pertinent to an industrial blast furnace. A total of eight objectives have been modeled using the operational data of the furnace using 12 process variables identified through a principal component analysis and optimized simultaneously. The capability of this algorithm to handle a large number of objectives, which has been lacking earlier, results in a more efficient setting of the operational parameters of the furnace, leading to a precisely optimized hot metal production process.     

Optimization of annealing cycle parameters of dual phase and interstitial free steels by multiobjective genetic algorithms

Data-driven models have been constructed for Dual Phase (DP) and Interstitials Free (IF) steels using an evolutionary approach. DP steel data are utilized from an existing database, while for the IF steels, data generated at an integrated steel plant have been used. The objective function for Ultimate Tensile Strength (UTS) and % elongation, created as data-driven models, is simultaneously optimized for an optimum strength-ductility balance and the results indicate the possibilities of developing steels with better mechanical properties than what are known to have been existing so far.     

TiB whisker coating on titanium surfaces by solid-state diffusion: Synthesis,microstructure, and mechanical properties

The study demonstrates the feasibility of synthesizing TiB whiskers on titanium (Ti) surfaces by solid-state diffusion to form a hard and wear-resistant coating. The microstructural and mechanical properties of the TiB coating layer have also been investigated. The TiB coating was formed by the solid-state diffusion of boron (B) from a powder mixture containing amorphous boron, Na₂CO₃ powder, and charcoal (activated) powder. The diffusion process was carried out at various temperatures ranging from 800 °C to 1000 °C for various periods of time ranging from 1 to 24 hours. The amount of Na₂CO₃ in the mixture was also varied. It has been found that pristine and extremely fine TiB whiskers form on the surfaces of titanium, with the whiskers growing more or less normal to the surface. A maximum coating thickness of about 218 μm was observed for the pack diffusion conditions at 850 °C for 24 hours with 15 pct Na₂CO₃. The kinetics of TiB formation was found to follow the growth rates in bulk composites. The X-ray diffraction (XRD) patterns of the coatings revealed the dominant TiB peaks with a very few TiB₂ peaks, with small intensity at higher temperature and time. The surface hardness of the coated layer increased to a Vickers hardness of about 550 kgf/mm² due to the presence of TiB whiskers in the coating. It is shown that pack diffusion of boron in the solid state is a simple and very effective means of generating hard and wear-resistant coatings on titanium.     

Thermodynamic mechanism of free heme action on sickle cell hemoglobin polymerization

For insights into the mechanisms of heme action on the rate of sickle cell hemoglobin polymerization, we determine the erythrocytic concentration of free heme using a novel method based on enzymatic catalysis and luminescence. We find in sickle cell patients 44 ± 10 µM, in sickle trait individuals, 33 ± 4 µM, and in healthy adults, 21 ± 2 µM. We test the applicability of two mechanisms of heme action: a kinetic one, whereby heme aggregates serve as heterogeneous nucleation centers, and a thermodynamic pathway, in which free heme enhances the attraction between sickle hemoglobin (HbS) molecules in solution. We show that the latter mechanism exclusively operates. The enhanced attraction leads to increase of the total volume of a population of dense liquid clusters by about two orders of magnitude. As the dense liquid clusters serve as locations and precursors to the formation of the HbS polymer nuclei, their increased volume directly leads to faster polymer nucleation. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2861–2870, 2015     

Cocoa Butter Substitute (CBS) Produced from Palm Mid-fraction/Palm Kernel Oil/Palm Stearin for Confectionery Fillings

This study investigated the physicochemical properties of ternary mixtures of palm mid-fraction (PMF):refined bleached deodorized palm kernel oil (RBDPKO):refined bleached deodorized palm stearin (RBDPS) for cocoa butter substitute (CBS). Fatty acid constituents, triacylglycerol constituents, solid fat contents (SFCs), melting behavior, polymorphism and crystal morphology were determined using gas chromatography (GC), high-performance liquid chromatography (HPLC), differential scanning calorimetry (DSC), pulsed nuclear magnetic resonance (p-NMR), X-ray diffraction (XRD) and polarized light microscopy (PLM), respectively. Eight blends of various ratios of ternary mixtures were investigated based on the previously studied binary fat mixtures. The composition of palmitic (P) and oleic (O), POP, and crystal morphology (size and shape) of the PMF/RBDPKO/RBDPS [14.9/59.6/25.5 (%w/w)] mixture were comparable to cocoa butter (CB), while its melting profile (18.5 and 37 °C), SFC at 20 °C and polymorphism were different from CB. The iso-solid diagrams of the mixture displayed a monotectic effect at 20–25 °C. Therefore, the 14.9/59.6/25.5 PMF/RBDPKO/RBDPS mixture could be used as a CBS in confectionery fillings because of the crystal morphology and monotectic behaviors comparable to those of CB.     

Self-organizing maps for pattern recognition in design of alloys

A combined experimental–computational methodology for accelerated design of AlNiCo-type permanent magnetic alloys is presented with the objective of simultaneously extremizing several magnetic properties. Chemical concentrations of eight alloying elements were initially generated using a quasi-random number generator so as to achieve a uniform distribution in the design variable space. It was followed by manufacture and experimental evaluation of these alloys using an identical thermo-magnetic protocol. These experimental data were used to develop meta-models capable of directly relating the chemical composition with desired macroscopic properties of the alloys. These properties were simultaneously optimized to predict chemical compositions that result in improvement of properties. These data were further utilized to discover various correlations within the experimental dataset by using several concepts of artificial intelligence. In this work, an unsupervised neural network known as self-organizing maps was used to discover various patterns reported in the literature. These maps were also used to screen the composition of the next set of alloys to be manufactured and tested in the next iterative cycle. Several of these Pareto-optimized predictions out-performed the initial batch of alloys. This approach helps significantly reducing the time and the number of alloys needed in the alloy development process.     

Dynamic process modelling of iron ore sintering

A mathematical model was developed for the iron ore sintering process considering all the major thermochemical phenomena in the system, assuming both the static and moving bed configurations. The model predicted a large number of parameters pertinent to the sintering process including the temperatures of the gas and solid, concentration of various species, amount of solid melted etc. The results were tested against the data existing in literature, and a limited number of pot tests conducted in a pilot plant. Despite high complexity of the problem, the agreement between the experimental and simulated data was reasonably good.     

Structural and morphological investigations on DC-magnetron-sputtered nickel films deposited on Si (100)

Pure nickel thin films were deposited on Si (100) substrates under different conditions of sputtering using direct current magnetron sputtering from a nickel metal target. The different deposition parameters employed for this study are target power, argon gas pressure, substrate temperature and substrate-bias voltage. The films exhibited high density of void boundaries with reduction in <111> texture deposited under high argon gas pressures. At argon gas pressure of 5 mTorr and target power of 300 W, Ni deposition rate was ~40 nm/min. In addition, coalescence of grains accompanied with increase in the film texture was observed at high DC power. Ni films undergo morphological transition from continuous, dense void boundaries to microstructure free from voids as the substrate-bias voltage was increased from −10 to −90 V. Furthermore, as the substrate temperature was increased, the films revealed strong <111> fiber texture accompanied with near-equiaxed grain structure. Ni films deposited at 770 K showed the layer-by-layer film formation which lead to dense, continuous microstructure with increase in the grain size.