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.     

A protein which masks galactose receptor mediated phage susceptibility in Lactococcus lactis subsp. lactis MPL56

A 28.5-kb plasmid, isolated from Lactococcus lactis subsp. lactis MPL56, causes complete inhibition of four lactococcal phages. Cell wall characteristics of wild-type strain MPL56 were compared with its 28.5 kb plasmid-cured, phage-sensitive derivative MPL56-22. After proteolytic enzyme treatments, adsorption of phages occurred at high levels, an example is 94.6–98.5% in MPL56 cells. Analysis of cell wall extracts of MPL56-22 by sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS–PAGE) indicated that the only difference between strains was the 55.4 kDa band in protein patterns of MPL56. Adsorption of the four phages was completely inhibited when MPL56-22 cells were subjected to SDS, Triton-X-100, HCl and NaOH treatments. Lectins that were specific for glucose/mannose and N-acetylglucosamine did not prevent adsorption of phages in cell wall extracts of MPL 56-22. However a lectin specific for galactose (MCA; Momordica charantia ) completely inhibited adsorption of these phages in cell wall extracts of MPL56-22. HPLC patterns of cell wall carbohydrates of MPL56-22 and its HCl treated preparations showed that the most prevalent difference was the galactose on untreated MPL56-22 cell wall chromatograms.     

Relation between abrasion resistance and flexural strength of high volume fly ash concrete

In this paper, abrasion of high volume fly ash (HVFA) concretes made with 50% and 70% of cement replacement with fly ash was assessed in terms of its relation to flexural tensile strength. Comparisons were made between normal Portland cement (NPC) concrete and fly ash concrete. Comparisons were also made between fly ash concretes. Investigation results have shown that the abrasion resistance increased as flexural tensile strength increased. Analysis of the results showed that, for concrete with tensile strength of greater than 4–5 MPa, the abrasion resistance of HVFA concrete with 70% replacement with cement was found to be higher than that of counterpart control NPC concrete and concrete made with 50% fly ash. The comparison between the relation of abrasion to compressive strength and abrasion to flexural tensile strength made in terms of R² of the linear regression showed that a stronger relation existed between abrasion and flexural tensile strength than that of abrasion to compressive strength of the concrete studied.

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Résumé L'étude a pour but d'estimer la relation entre la résistance à l'usure avec la résistance à la traction en flexion des bétons contenant de 50% et 70% de cendres volantes. On a comparé le béton pur au béton contenant des cendres volantes. Des comparaisons ont été faites également entre les différents bétons contenant des cendres volantes. Les resultats de la recherche ont montré que la résistance à l'usure augmente à mesure que la résistance à la traction en flexion de 4∼5 MPa ont une résistance à l'usure plus grande s'ils contienneint 70% de cendres volantes que s'ils étaient purs ou contenaient 50% de cendres volantes. La comparaison entre les relation de la résistance à l'usure en compression et de la résistance à l'usure en traction a été établie en termes de R² de la régression linéaire. On a prouvé qu'une relation plus forte a été obtenue entre la résistance à l'usure et la résistance à la traction en flexion par rapport à la résistance à l'usure en compression du béton étudié.

     

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.     

A method for preparing collagen graft materials

The aim of this research was to develop a method of local production of collagen graft materials which are presently imported. The following methods were used to produce collagen membrane and sponge from human placentas and rat tail tendons. Collagen type I was isolated from human placenta and rat tail tendon by acetic acid extraction and characterised by SDS-PAGE. The collagen sponge was prepared by dissolving the collagen in HCl. The resulting dispersion was poured into a glass container, freeze-dried and then cross-linked by immersion in glutaraldehyde solution. It was then washed with distilled water and freeze-dried again. The collagen membrane was also similarly prepared by dispersing lyophilized collagen in HCl but then mixed with glutaraldehyde, exposed to U.V. light and later air dried.     

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.