Thermal stresses during electro-chemical spark machining
The high temperature distribution generated during electro-chemical spark machining (ECSM) results in large localised thermal stresses in a very small heat affected zone. These thermal stresses can lead to micro-cracks and a decrease in strength and fatigue life of the components. A finite element model is developed to estimate the temperature distribution and thermal stresses due to a single spark (Gaussian distributed heat flux) and within the zone of influence of a single spark. Firstly, the finite element based (FEM) code is developed to estimate temperature distribution in the workpiece due to a single spark and, based on this temperature distribution, thermal stresses are calculated. Thermal stress analysis shows high temperature gradient zones and the regions of large stresses where, sometimes, they exceed the material yield strength.
Experimental Investigations into Traveling Wire Electrochemical Spark Machining (TW-ECSM) of Composites
Experiments are carried out on glass-epoxy and kevlar-epoxy composites, using sodium hydroxide (NaOH) as electrolyte. The wire and the workpiece were kept in physical contact with each other by the use of a gravity feed mechanism. The effects of voltage and concentration of the electrolyte on material removal rate, average diametral overcut, tool wear rate, and wire erosion ratio are reported
To What Extent Can English-as-a-Second Language Learners Read Economic News Texts?
In decision making in the economic field, an especially important requirement is to rapidly understand news to absorb ever-changing economic situations. Given that most economic news is written in English, the ability to read such information without waiting for a translation is particularly valuable in economics in contrast to other fields. In consideration of this issue, this research investigated the extent to which non-native English speakers are able to read economic news to make decisions accordingly – an issue that has been rarely addressed in previous studies. Using an existing standard dataset as training data, we created a classifier that automatically evaluates the readability of text with high accuracy for English learners. Our assessment of the readability of an economic news corpus revealed that most news texts can be read by intermediate English learners. We also found that in some cases, readability varies considerably depending on the knowledge of certain words specific to the economic field.