Microgravity

This is a computer generated model of a ground based casting. The objective of the therophysical properties program is to measure thermal physical properties of commercial casting alloys for use in computer programs that predict soldification behavior. This could reduce trial and error in casting design and promote less scrap, sounder castings, and less weight. In order for the computer models to reliably simulate the details of industrial alloy solidification, the input thermophysical property data must be absolutely reliable. Recently Auburn University and TPRL Inc. formed a teaming relationship to establish reliable measurement techniques for the most critical properties of commercially important alloys: transformation temperatures, thermal conductivity, electrical conductivity, specific heat, latent heat, density, solid fraction evolution, surface tension, and viscosity. A new initiative with the American Foundrymens Society has been started to measure the thermophysical properties of commercial ferrous and non-ferrous casting alloys and make the thermophysical property data widely available. Development of casting processes for the new gamma titanium aluminide alloys as well as existing titanium alloys will remain a trial-and-error procedure until accurate thermophysical properties can be obtained. These molten alloys react with their containers on earth and change their composition - invalidating the measurements even while the data are being acquired in terrestrial laboratories. However, measurements on the molten alloys can be accomplished in space using freely floating droplets which are completely untouched by any container. These data are expected to be exceptionally precise because of the absence of impurity contamination and buoyancy convection effects. Although long duration orbital experiments will be required for the large scale industrial alloy measurement program that results from this research, short duration experiments on NASA's KC-135 low-g aircraft are already providing preliminary data and experience.