In this study a number of work-piece variations were evaluated whilst limiting the cutting conditions. Eight wood species controlled at four moisture levels were machined along and across the wood grain. The tool used during cutting was designed to resemble a rip saw tooth with zero rake angle and narrow edge width. Each work-piece variation machined in the cutting tests was subjected to mechanical tests that evaluated bending properties across the grain and shear properties along the grain. The regression model establishes a relationship between the bending properties for cutting forces across the grain, as well as shear properties for cutting forces along the grain. F and R² values show that the elastic properties of the wood in bending and shear have less influence on the cutting forces when compared to the strength and toughness. Additionally, density is seen to have less influence on the cutting force along the grain. This is explained by the tool passing through an unquantifiable proportion of early and latewood fibers from the annual growth rings. Cutting across the grain, the tool is forced to machine through approximately the same proportion of earlywood and latewood fibres.
Purpose
The purpose of this paper is to present a novel model for predicting the effective viscosity of nanofluids. At present, no unified model exists for the same.
Design/methodology/approach
The present effective viscosity model draws upon the regression analysis of carefully selected published papers covering experimental, numerical and theoretical findings.
Findings
Unlike some other models, this one is reliable and has a good level of accuracy. This model has been assessed in a numerical investigation using a 3D horizontal pipe, and the results are presented.
Originality/value
This is a new model for predicting the effective viscosity of nanofluids. The proposed model has been tested in a 3D horizontal pipe, and the predicted results for viscosity and Nusselt number show good agreement with the available data.
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