Predictive Models for the Velocity of Sound in Liquid Metallic Elements at Their Melting-Point Temperatures

Abstract

Nowadays, accurate and reliable data for the thermophysical properties of almost all liquid metallic elements are indispensable in the field of materials process science (e.g., for computer simulation studies of the fluid flow in a vessel or the solidification of a metallic element). The dimensionless common parameters (denoted by ξ 1/2 and ξ 1/2 ), extracted from the velocity of sound, provide for better predictions of the thermophysical properties of liquid metallic elements such as surface tension, viscosity, self-diffusion, thermal expansion, and evaporation enthalpy, because these two parameters characterize the state of the liquid metallic atom (i.e., an atom’s hardness or softness and its anharmonic motions). The usefulness of reliable predictive models in many engineering situations is clear; in the field of materials process science and engineering, both “accuracy” and “universality” are required of any model for predicting the thermophysical properties of liquid metallic elements. In view of the accuracy and universality of a model, predictive models for the velocity of sound in liquid metallic elements at their melting-point temperatures were investigated; the performances of several models were evaluated by comparing experimental values for the melting-point sound velocity in various liquid metallic elements with those calculated from these models, using a relative standard deviation as a yardstick. Of these, two simple models in terms of well-known physical quantities, presented by the authors, give very good agreement with the experimental data. Excluding only a few metals, calculated sound-velocity values fall, or almost fall, within the range of uncertainties associated with experimental measurements of high-melting-point or reactive metals. It can safely be said that the two models for melting-point sound velocity in liquid metallic elements are endowed with the necessary conditions of being predictive.