Removal of Hydrogen and Solid Particles from Molten Aluminum Alloys in the Rotating Impeller Degasser: Mathematical Models and Computer Simulations

Aluminum alloy cleanliness has been in the limelight during the last three decades and still remains as one of the top concerns in the aluminum casting industry. In general, cleaning an aluminum alloy refers to minimizing the following contaminants: 1) dissolved gases, especially hydrogen, 2) alkaline elements, such as sodium, lithium, and calcium, and 3) unwanted solid particles, such as oxides, carbides, and a variety of intermetallic compounds. Extensive research has resulted in significant improvements in our understanding of the various aspects of these contaminants, and in many foundries, melt-cleansing practices have been established and are routinely used. However, with the ever-increasing demands for improved casting properties, requirements for molten metal cleanliness has become extremely stringent. Rotary degassing is one of the most efficient ways of cleansing molten metals, thus removal of unwanted particles and dissolved hydrogen from molten aluminum alloys by rotary degassing has become a widely used foundry practice. Rotary degassing involves purging a gas into the molten alloy through holes in a rotating impeller. Monatomic dissolved hydrogen either diffuses into these gas bubbles or it forms diatomic hydrogen gas at the bubbles’ surface; in any case, it is removed from the melt with the rising bubbles. Simultaneously, solid particles in the melt collide with one another due to turbulence created by the impeller and form aggregates. These aggregates either settle to the furnace floor, or are captured by the rising gas bubbles and are also removed from the melt. The objective of this work is to understand the physical mechanisms underlying the removal of dissolved hydrogen and unwanted solid particles from molten aluminum alloys by the rotating impeller degasser, and to develop a methodology for the effective use of the degassing process by providing mathematical models and computer simulations of the process. The models and simulations can be used to optimize the process, design new equipment and determine the cause of specific operational problems