Occurrence Of Expulsion Research Articles

THE EFFECT OF PERIODICALLY "MILKING" TO OBTAIN TYRIAN PURPLE FROM PLICOPURPURA PANSA (GOULD, 1853) ON THE FREQUENCY OF EXPULSION AND MORTALITY

Abstract Most marine snails of the families Muricidae and Thaididae produce in their hypobranchial gland (mucus gland) a colorless secretion containing minute amounts of chromogens, which develop under the influence of light and oxygen into a pigment known as “Tyrian Purple.” The hypobranchial gland of Plicopurpura pansa (Gould, 1853) is an exception among the muricids, because it is so active the snails can be stimulated periodically to expulse the secretion without harming the animals. In view of reported drastic declines of the populations of P. pansa because of the Tyrian Purple exploitation, in this laboratory study the effect of periodically “milking” of P. pansa on the frequency of expulsion and on the mortality of the snails was determined. At the beginning of the experiment using 110 animals (55 males and 55 females) only 30% expelled secretion. No relation was found between the occurrence of expulsion and the size or sex of the animals. In contrast to the laboratory snails the proportion of expu...

Expulsion detection system for resistance spot welding based on a neural network

Resistance spot welding is one of the most important welding procedures. Therefore, a strong emphasis is placed on the quality of the welds. One of the phenomena that causes the deterioration in quality is the eruption of molten material, the so-called expulsion. Expulsion can be avoided with appropriate parameter selection. The problem, however, lies in the fact that the best quality welds are made with parameters just below the expulsion area. Therefore, for any successful control scheme an efficient and dependable expulsion detection is needed. A linear vector quantization (LVQ) neural network system is proposed to achieve this goal. The network is analysed with different sensor combinations and different materials. The results show that the LVQ neural network is able to detect the expulsion in different materials. The experiment also points to the welding force signal as the most important indicator of the expulsion occurrence.

A Statistical Analysis of Expulsion Limits in Resistance Spot Welding

Expulsion is an important phenomenon in resistance spot welding. It involves loss of metal from the liquid nugget, which often results in the reduction of weld strength. Various models have been proposed to understand expulsion mechanisms. In these models the occurrence of expulsion is often treated as a deterministic event, and depicted by a line (boundary) in conventional lobe diagrams. In this study, statistical analysis is employed to explore expulsion with consideration of the influence of random factors. Models are built based on experimental data, and one steel and two aluminum alloys are used as examples. Expulsion probabilities are presented as a function of electrode force, welding current, and time. Analytical models and their graphical form of expression (contours and surfaces) are created to present expulsion limits under various combinations of welding parameters. This study provides not only quantitative model predictions on expulsion limits for the materials studied, but also a generic statistical methodology that can be used for analyzing expulsion in various material systems. [S1087-1357(00)00602-X]