Influence of Bottom Bubbling Rate on Formation of Metal Emulsion in Al-Cu Alloy and Molten Salt System

In steel refining process, an increase of interfacial area between the metal and slag through the metal droplets emulsified into the slag, so-called ``metal emulsion'', is one prevailing view for improving the reaction rate. The formation of metal emulsion was experimentally evaluated using Al-Cu alloy as metal phase and chloride salt as slag phase under the bottom bubbling condition. Samples were collected from the center of the salt phase in the container. Large number of metal droplets were separated from the salt by dissolving it into water. The number, surface area, and weight of the droplets increased with the gas flow rate and have local maximum values. The formation and sedimentation rates of metal droplets were estimated using a mathematical model. The formation rate increased with the gas flow rate and has a local maximum value as a function of gas flow rate, while the sedimentation rate is independent of the gas flow rate under the bottom bubbling condition. Three types of formation mode of metal emulsion, which occurred by the rupture of metal film around the bubble, were observed using high speed camera. During the process, an elongated column covered with metal film was observed with the increasing gas flow rate. This elongated column sometimes reached to the top surface of the salt phase. In this case, it is considered that fine droplets were not formed and in consequence, the weight of metal emulsion decreased at higher gas flow rate.

An invariant subspace-based approach to the random eigenvalue problem of systems with clustered spectrum

The repeated or closely spaced eigenvalues and corresponding eigenvectors of a matrix are usually very sensitive to a perturbation of the matrix, which makes capturing the behavior of these eigenpairs very difficult. Similar difficulty is encountered in solving the random eigenvalue problem when a matrix with random elements has a set of clustered eigenvalues in its mean. In addition, the methods to solve the random eigenvalue problem often differ in characterizing the problem, which leads to different interpretations of the solution. Thus, the solutions obtained from different methods become mathematically incomparable. These two issues, the difficulty of solving and the non-unique characterization, are addressed here. A different approach is used where instead of tracking a few individual eigenpairs, the corresponding invariant subspace is tracked. The spectral stochastic finite element method is used for analysis, where the polynomial chaos expansion is used to represent the random eigenvalues and eigenvectors. However, the main concept of tracking the invariant subspace remains mostly independent of any such representation. The approach is successfully implemented in response prediction of a system with repeated natural frequencies. It is found that tracking only an invariant subspace could be sufficient to build a modal-based reduced-order model of the system. Copyright (C) 2012 John Wiley & Sons, Ltd.