Modeling and simulation of a fully air swept ball mill in a raw material grinding circuit

A raw material grinding circuit was modeled using plant data. Samples were collected from around the circuit and, following a crash stop, from inside the mill. The size distributions of the samples were determined down to a few microns. Using the data from inside the mill a modeling approach, based on perfect mixing, was developed. The modelling approach implicitly assumes that the mixture of feed materials broken is homogenous from the breakage point of view. The air classification around the circuit was modeled using the efficiency curve approach. In order to measure the success of the method the circuit performance was predicted by simulation studies while it was operating at different conditions. The results were then compared with the measured data. It is concluded that modeling gives a useful quantitative indication of what may occur in fully air swept mills.     

THE ELECTROIMPACT COMPACTION OIF POWDERS: MECHANICS, STRUCTURE AND PROPERTIES

An electroimpact compaction method recently developed for powder consolidation is described In terms of the basic principles of electric discharge and dynamic compaction processes. The influence of processing parameters, microstructural characteristics and mechanical properties of preforms obtained are discussed. Mathematical models for the mechanics of compaction, electrical resistance, discharge current variations and comparisons with experimental results are presented. The best set of properties are obtained when electrical discharge is applied to cause interparticle fusion at the instant when dynamic compaction pressure attains its peak level.     

Alumina scale growth at zirconia-MCrAlY interface: a microstructural study

High-temperature oxide scale growth at the ceramic-metal interface is a major contributor to the thermomechanical resistance of thermal barrier coatings for hot stages of gas turbines. In order to better understand this phenomenon, microstructural observations of the alumina scales formed at 1100 and 1200 °C under air, between low-pressure plasma-sprayed NiCrAlY and air plasma-sprayed ZrO₂-8.5 wt % Y₂O₃, have been performed by classical and analytical transmission electron microscopy on transverse thin foil specimens. The evolution of the oxide grain morphology from the metal-oxide to the oxide-oxide interface suggests that the scale growth principally takes place at the metal-oxide interface. Segregation of yttrium at oxide grain boundaries has been detected as well as significant quantities of zirconium inside the alumina grains. The oxide growth seems to be dominated by a classical grain-boundary oxygen diffusion mechanism. The presence of zirconium inside the alumina grains also suggests that Al₂O₃ partially forms by chemical reduction of ZrO₂ by AI. The comparison between the microstructures observed and that of alumina scales grown under similar conditions on bare MCrAlY alloys gives some insight into how the ceramic top-coat modifies NiCrAlY high-temperature oxidation mechanisms.     

Poly-functional Catalyst Development for Benzene Production from Alkyl-aromatic Mixture via Hydrodealkylation

Development of a poly-functional catalyst that has higher hydrodealkylation activity based on 15% Cr/γ- Al₂ O₃ was researched for benzene production from an alkyl-aromatic mixture via hydrodealkylation. For this goal, the effects of the promoters like Fe, Co, or Ni and their concentrations on the activity of a Cr/Al₂ O₃ catalyst were investigated. Toluene + n-heptane + tetrahydrotiophene (89:10:1 w%) model mixture, which has the same content as industrial aromatics, was used as feedstock. The activities of catalysis in reactions of hydrodealkylation, hydrocracking, and hydrogenolize with respect to conversions of toluene, heptane, and tetrahydrotiophene were tested, respectively. As to the obtained results, the catalyst including 5% Fe has a higher hydrodealkylation activity, compared to the catalyst including Co, and especially to the alumocrom catalyst not including a promoter, while it has a lower coke formation and reduced activity to the catalyst including Ni.     

Vibrations of stretched damped beams under non-ideal boundary conditions

A simply supported damped Euler-Bernoulli beam with immovable end conditions are considered. The concept of non-ideal boundary conditions is applied to the beam problem. In accordance, the boundaries are assumed to allow small deflections and moments. Approximate analytical solution of the problem is found using the method of multiple scales, a perturbation technique.     

An experimental study on the performance parameters of an experimental CI engine fueled with diesel-methanol-dodecanol blends

The effects of using diesel-methanol-dodecanol blends including methanol of various proportions on a CI engine performance are experimentally investigated. The methanol concentration in the blend has been changed from 2.5% to 15% with the increments of 2.5%, and 1% dodecanol was added into each blend to solve the phase separation problem. Experimental study has been conducted on a single-cylinder, water-cooled CI engine. The engine has been operated at different compression ratios (19, 21, 23 and 25) and the engine speed was varied from 1000 to 1600 rpm at each compression ratio. The performance parameters such as torque, effective power, specific fuel consumption and effective efficiency for each blend at various conditions are calculated depending on the experimental data. It was concluded that among the different blends, the blend including 10% methanol (DM10) is the most suited one for CI engines from the engine performance point of view. Improvements obtained up to 7% in performance parameters with this blend without any modification to engine design and fuel system are very promising.     

Multi-objective mixture design and optimisation of steel fiber reinforced UHPC using machine learning algorithms and metaheuristics

Ultra-high-performance concrete (UHPC) is a recent class of concrete with improved durability, rheological and mechanical and durability properties compared to traditional concrete. The production cost of UHPC is considerably high due to a large amount of cement used, and also the high price of other required constituents such as quartz powder, silica fume, fibres and superplasticisers. To achieve specific requirements such as desired production cost, strength and flowability, the proportions of UHPC’s constituents must be well adjusted. The traditional mixture design of concrete requires cumbersome, costly and extensive experimental program. Therefore, mathematical optimisation, design of experiments (DOE) and statistical mixture design (SMD) methods have been used in recent years, particularly for meeting multiple objectives. In traditional methods, simple regression models such as multiple linear regression models are used as objective functions according to the requirements. Once the model is constructed, mathematical programming and simplex algorithms are usually used to find optimal solutions. However, a more flexible procedure enabling the use of high accuracy nonlinear models and defining different scenarios for multi-objective mixture design is required, particularly when it comes to data which are not well structured to fit simple regression models such as multiple linear regression. This paper aims to demonstrate a procedure integrating machine learning (ML) algorithms such as Artificial Neural Networks (ANNs) and Gaussian Process Regression (GPR) to develop high-accuracy models, and a metaheuristic optimisation algorithm called Particle Swarm Optimisation (PSO) algorithm for multi-objective mixture design and optimisation of UHPC reinforced with steel fibers. A reliable experimental dataset is used to develop the models and to justify the final results. The comparison of the obtained results with the experimental results validates the capability of the proposed procedure for multi-objective mixture design and optimisation of steel fiber reinforced UHPC. The proposed procedure not only reduces the efforts in the experimental design of UHPC but also leads to the optimal mixtures when the designer faces strength-flowability-cost paradoxes.