Kaiser Aluminum

About: Kaiser Aluminum is a based out in . It is known for research contribution in the topics: Alloy & Corrosion. The organization has 546 authors who have published 504 publications receiving 6554 citations. The organization is also known as: Kaiser Aluminum and Chemicals.

Particulate material treatment system and conveyor belt mixing system

Abstract: A system and a process is provided for reducing the dust formation during the transfer of a particulate material on an endless conveyor belt. During transfer of the material on the conveyor belt the material is first sprayed with a wetting agent then by application of a plow the moving material is lifted from the bottom of the belt and is diverted towards the side edges of the belt thus creating additional exposed surfaces. The material is then again sprayed then contacted with baffles to redirect the material from the side edges towards the center of the belt thus creating additional exposed surfaces which are then again sprayed with a wetting agent to substantially eliminate dusting. The plow and baffle combination can also be used for uniformly mixing two or more particulate materials on a moving belt.

Composition control of an electrocoating bath

Abstract: This invention relates to a method of controlling the composition of an electrocoating bath, and, in particular, the neutralization agent content of such a bath wherein the electrocoating current is sensed and in accordance therewith a particular amount of ultrafilter permeate is discarded.

Adaptive control of feed in the Hall-Héroult cell using a neural network

Abstract: A linear neural network is proposed for estimating alumina concentration in an aluminum reduction cell. Bath resistance/alumina concentration data from a simulated 140 kA Center-Break Hall-Heroult cell were used as input vectors to train a two-layer neural network constructed with six constraints and six degrees of freedom. Results from simulated and real data tests using the derived estimation algorithm are presented. Also, neural network is compared with extended Kalman filter and shown to have a superior performance in the estimation problem. Finally, the paper claims robustness for the neural algorithm against changes in resistance due to cell events like tapping and anode change.

Self-centering bottom block assembly

Abstract: This invention relates to a self-centering bottom block for a direct chill (D.C.) casting apparatus. The assembly comprises a bottom block which is slidably mounted on a supporting surface and a retaining ring which loosely locks the bottom block to the supporting surface but which allows for the horizontal movement of the bottom block. As the assembly is raised into position, guide buttons on the exterior surfaces of the assembly ride on guide surfaces which are fixed spatially with respect to the mold bore and thereby center the assembly within the mold bore. In another embodiment of the invention, the bottom block assembly is provided with a means which engages the ingot during the initial phases of solidification and urges the ingot during the initial phases of solidification and urges the ingot out of the mold but which readily disengages the ingot after casting.