Fracture toughness determination of adhesive and co-cured joints in natural fibre composites

Adhesive bonding has become more efficient in the last few decades due to the adhesives developments, granting higher strength and ductility. On the other hand, natural fibre composites have recently gained interest due to the low cost and density. It is therefore essential to predict the fracture behavior of joints between these materials, to assess the feasibility of joining or repairing with adhesives. In this work, the tensile fracture toughness (Gc n) of adhesive joints between natural fibre composites is studied, by bonding with a ductile adhesive and co-curing. Conventional methods to obtain Gc n are used for the co-cured specimens, while for the adhesive within the bonded joint, the J-integral is considered. For the J-integral calculation, an optical measurement method is developed for the evaluation of the crack tip opening and adherends rotation at the crack tip during the test, supported by a Matlab sub-routine for the automated extraction of these quantities. As output of this work, an optical method that allows an easier and quicker extraction of the parameters to obtain Gc n than the available methods is proposed (by the J-integral technique), and the fracture behaviour in tension of bonded and co-cured joints in jute-reinforced natural fibre composites is also provided for the subsequent strength prediction. Additionally, for the adhesively- bonded joints, the tensile cohesive law of the adhesive is derived by the direct method.

A Review on the Characterization of Signals and Systems by Power Law Distributions

Power laws, also known as Pareto-like laws or Zipf-like laws, are commonly used to explain a variety of real world distinct phenomena, often described merely by the produced signals. In this paper, we study twelve cases, namely worldwide technological accidents, the annual revenue of America׳s largest private companies, the number of inhabitants in America׳s largest cities, the magnitude of earthquakes with minimum moment magnitude equal to 4, the total burned area in forest fires occurred in Portugal, the net worth of the richer people in America, the frequency of occurrence of words in the novel Ulysses, by James Joyce, the total number of deaths in worldwide terrorist attacks, the number of linking root domains of the top internet domains, the number of linking root domains of the top internet pages, the total number of human victims of tornadoes occurred in the U.S., and the number of inhabitants in the 60 most populated countries. The results demonstrate the emergence of statistical characteristics, very close to a power law behavior. Furthermore, the parametric characterization reveals complex relationships present at higher level of description.

Casualties distribution in human and natural hazards

Catastrophic events, such as wars and terrorist attacks, big tornadoes and hurricanes, huge earthquakes, tsunamis, floods, and landslides, are always accompanied by a large number of casualties. The size distribution of these casualties have separately been shown to follow approximate power law (PL) distributions. In this paper, we analyze the number of victims of catastrophic phenomena, in particular, terrorism, and find double PL behavior. This means that the data set is better approximated by two PLs instead of one. We have plotted the two PL parameters corresponding to all terrorist events occurred in every year, from 1980 to 2010. We observe an interesting pattern in the chart, where the lines, that connect each pair of points defining the double PLs, are roughly aligned to each other.