The temperature dependence of effective thermal conductivity of open-celled steel alloy foams

The effective thermal conductivity of steel alloy FeCrAlY (Fe-20 wt.% Cr-5 wt.% Al-2 wt.% Y-20 wt.%) foams with a range of pore sizes and porosities was measured between 300 and 800 K, under both vacuum and atmospheric conditions. The results show that the effective thermal conductivity increases rapidly as temperature is increased, particularly in the higher temperature range (500-800 K) where the transport of heat is dominated by thermal radiation. The effective conductivity at temperature 800 K can be three times higher than that at room temperature (300 K). Results obtained under vacuum conditions reveal that the effective conductivity increases with increasing pore size or decreasing porosity. The contribution of natural convection to heat conduction was found to be significant, with the effective thermal conductivity at ambient pressure twice the value of vacuum condition. The results also show that natural convection in metal foams is strongly dependent upon porosity. © 2003 Elsevier B.V. All rights reserved.

Wastage of low alloy steels in a fluidized bed environment

The wastage behaviour of four low alloy steels, suitable for use as evaporator tubing in industrial atmospheric fluidized bed combustors (AFBCs), was examined in a laboratory-scale test rig. Specimens exposed in the test apparatus experienced a high flux of impacts at low particle velocities similar to conditions in a FBC boiler. The influence of time, velocity and temperature on the wastage behaviour was examined and incubation times and velocity exponents were determined and their values discussed. Since high-temperature oxidation played an important role in this process, the short-term oxidation rate of each of the steels was measured. The mechanisms of material loss across the temperature range were discussed and the behaviour of the low alloy steels in the current work was compared with that of high alloy and stainless steels in earlier studies. © 1995.

Model for solidification cracking in low alloy steel weld metals

Data on the occurrence of solidification cracking in low alloy steel welds have been analysed using a classification neural network based on a Bayesian framework. It has thereby been possible to express quantitatively the effect of variables such as the chemical composition, welding conditions, and weld geometry, on the tendency for solidification cracking during solidification. The ability of the network to express the relationship in a suitably non-linear form is shown to be vital in reproducing known experimental phenomena. © 1996 The Institute of Materials.