All ETDs from UAB

Advisory Committee Chair

Charles A Monroe

Advisory Committee Members

Haibin Ning

Laurentiu Nastac

Manoj Mahapatra

Mohammad Haider

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) School of Engineering


RAPID MELTING OF ALUMINUM ALLOYS BY INDUCTION MELTING CARLOS ALFONSO LARRAZABAL COLINA MATERIAL SCIENCE AND ENGINEERING ABSTRACT Die-casting and high-pressure die-casting are manufacturing processes meant to produce high volumes of parts. However, the die-casting industry suffers when the market is low or when short quantities of a part are needed, because this process may not be as flexible in small quantities. In such situations, one piece of the operation that is inflexible is running excess melting and holding furnace capacity. Rapid induction melting systems are proposed here as an alternative to big furnaces to provide amounts of molten metal in short intervals so die-casting of small batches becomes economically feasible. Miniaturizing induction furnaces means that the melting process is done at higher frequencies than those utilized for commercial induction furnaces. To validate the utilization of a small, high-frequency induction furnace, an experimental apparatus was developed from a 10 kW induction-melting unit. The original equipment was instrumented to measure and record energies at every component of the melting unit so comprehensive energy efficiency analysis could be performed. In parallel, a two-way coupled Finite Element model was built to study the governing parameters in induction melting such as alloy, current, frequency, slenderness ratio, and mass/size. Additionally, the methodology also studies preheating as a mechanism to reduce melting time and increase efficiency. A commercial Finite Element software was utilized to developing the computational model with thermal feedback to account for the thermal dependent material properties. The model was parametrized such that all dimensions, material properties, and simulation conditions can be adjusted to study a wide variety of scenarios. The model was then used to create computational data consolidated into a regression analysis to study the effect of the defined governing parameters on the melting time and delta temperature differences in the sample; the latter reflects the difference in temperature between the surface and the center of the aluminum billet under study. Melting time and delta temperature were utilized as the control parameters for evaluating rapid melting systems. The computational model was evaluated by comparing the computational with the experimental coil energy efficiency and the melting times predicted by the model with the actual melting time of a set of experiments.

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