Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351

In this work, different artificial neural networks (ANN) are developed for the prediction of surface roughness (R a) values in Al alloy 7075-T7351 after face milling machining process. The radial base (RBNN), feed forward (FFNN), and generalized regression (GRNN) networks were selected, and the data used for training these networks were derived from experiments conducted using a high-speed milling machine. The Taguchi design of experiment was applied to reduce the time and cost of the experiments. From this study, the performance of each ANN used in this research was measured with the mean square error percentage and it was observed that FFNN achieved the best results. Also the Pearson correlation coefficient was calculated to analyze the correlation between the five inputs (cutting speed, feed per tooth, axial depth of cut, chip°s width, and chip°s thickness) selected for the network with the selected output (surface roughness). Results showed a strong correlation between the chip thickness and the surface roughness followed by the cutting speed. © ASM International.

Numerical Investigation of the Effect of Magnetic Field on Natural Convection in a Curved-Shape Enclosure

This investigation reports the magnetic field effect on natural convection heat transfer in a curved-shape enclosure. The numerical investigation is carried out using the control volume-based-finite element method (CVFEM). The numerical investigations are performed for various values of Hartmann number and Rayleigh number. The obtained results are depicted in terms of streamlines and isotherms which show the significant effects of Hartmann number on the fluid flow and temperature distribution inside the enclosure. Also, it was found that the Nusselt number decreases with an increase in the Hartmann number.

Wind Shear, Gust, and Yaw-Induced Dynamic Stall on Wind-Turbine Blades

This study examined the effect of a spanwise angle of attack gradient on the growth and stability of a dynamic stall vortex in a rotating system. It was found that a spanwise angle of attack gradient induces a corresponding spanwise vorticity gradient, which, in combination with spanwise flow, results in a redistribution of circulation along the blade. Specifically, when modelling the angle of attack gradient experienced by a wind turbine at the 30% span position during a gust event, the spanwise vorticity gradient was aligned such that circulation was transported from areas of high circulation to areas of low circulation, increasing the local dynamic stall vortex growth rate, which corresponds to an increase in the lift coefficient, and a decrease in the local vortex stability at this point. Reversing the relative alignment of the spanwise vorticity gradient and spanwise flow results in circulation transport from areas of low circulation generation to areas of high circulation generation, acting to reduce local circulation and stabilise the vortex. This circulation redistribution behaviour describes a mechanism by which the fluctuating loads on a wind turbine are magnified, which is detrimental to turbine lifetime and performance. Therefore, an understanding of this phenomenon has the potential to facilitate optimised wind turbine design.

DEVELOPMENT OF A MECHANISM AND PROCESS TO CONTINUOUSLY PRODUCE SPHERICAL, TORREFIED BIOMASS PELLETS

A recently developed novel biomass fuel pellet, the Q’ Pellet, offers significant improvements over conventional white pellets, with characteristics comparable to those of coal. The Q’ Pellet was initially created at bench scale using a proprietary die and punch design, in which the biomass was torrefied in-situ¬ and then compressed. To bring the benefits of the Q’ Pellet to a commercial level, it must be capable of being produced in a continuous process at a competitive cost. A prototype machine was previously constructed in a first effort to assess continuous processing of the Q’ Pellet. The prototype torrefied biomass in a separate, ex-situ reactor and transported it into a rotary compression stage. Upon evaluation, parts of the prototype were found to be unsuccessful and required a redesign of the material transport method as well as the compression mechanism. A process was developed in which material was torrefied ex-situ and extruded in a pre-compression stage. The extruded biomass overcame multiple handling issues that had been experienced with un-densified biomass, facilitating efficient material transport. Biomass was extruded directly into a novel re-designed pelletizing die, which incorporated a removable cap, ejection pin and a die spring to accommodate a repeatable continuous process. Although after several uses the die required manual intervention due to minor design and manufacturing quality limitations, the system clearly demonstrated the capability of producing the Q’ Pellet in a continuous process. Q’ Pellets produced by the pre-compression method and pelletized in the re-designed die had an average dry basis gross calorific value of 22.04 MJ/kg, pellet durability index of 99.86% and dried to 6.2% of its initial mass following 24 hours submerged in water. This compares well with literature results of 21.29 MJ/kg, 100% pellet durability index and <5% mass increase in a water submersion test. These results indicate that the methods developed herein are capable of producing Q’ Pellets in a continuous process with fuel properties competitive with coal.