4.7 Article

Methodology for predicting spray quenching of thick-walled metal alloy tubes

期刊

INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
卷 55, 期 11-12, 页码 2953-2964

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijheatmasstransfer.2012.02.018

关键词

Spray cooling; Quenching; Boiling curve

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This paper explores the parametric influences of spray quenching for thick-walled metal alloy tubes. Using the point-source depiction of a spray, an analytical model is derived to determine the shape and size of the spray impact zone, as well as the distribution of volumetric flux across the same zone. This distribution is incorporated into heat transfer correlations for all spray boiling regimes to generate a complete boiling curve for every location across the impact zone. By setting boundary conditions for both the sprayed and unsprayed portions of the tube surface, a heat diffusion model is constructed for a unit cell of the tube for both aluminum alloy and steel. This model is used to construct spray quench curves for every point along the sprayed surface and within the wall. Increasing nozzle pressure drop or decreasing orifice-to-surface distance are shown to increase the magnitude of volumetric flux, which hastens the onset of the rapid cooling stages of the quench as well as improves overall cooling effectiveness. The sprayed surface is characterized by fast thermal response to the spray, while regions within the wall display more gradual response due to heat diffusion delays. With their superior thermal diffusivity, aluminum alloy tubes transmit the cooling effect through the wall faster than steel tubes. For steel, the cooling effect is more concentrated near the sprayed surface, causing the sprayed surface to cool much faster and locations within the wall much slower than for aluminum alloy. The predictive approach presented in this paper facilitates the determination of surface temperature gradients in the quenched part to guard against stress concentration. Also, when combined with metallurgical transformation models for the alloy, it may be possible to predict material properties such as hardness and strength. (C) 2012 Elsevier Ltd. All rights reserved.

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