Calculation of thermal conductivity for alloy steels

The quantitative relationship between thermal conductivity and chemical compositions for alloy steels is established by multivariate linear regression. The contents of silicon and carbon, the total contents of strong carbide-and non-carbide-forming elements are reasonably selected as four independent variables for the regression method. It is shown that silicon has much stronger negative influence on the thermal conductivity of these steels than the transition elements due to the prominent difference in the outer shell electronic structures of silicon and iron. Carbon has positive influence on the thermal conductivity, because the addition of carbon will attract more carbide-forming elements partitioned into carbide, thus weakening their influence on the thermal conductivity of steel matrix.