Cyclone intensity categories

The weather forecast centers in Australia and many other countries use a scale of cyclone intensity categories (categories 1-5) in their cyclone advisories, which are considered to be indicative of the cyclone damage potential. However, this scale is mainly based on maximum gust wind speeds. In a recent research project involving computer modeling of cyclonic wind forces on roof claddings and fatigue damage to claddings, it was found that cyclone damage not only depends on the maximum gust wind speed, but also on two other cyclone parameters, namely, the forward speed and radius to maximum winds. This paper describes the computer model used in predicting the cyclone damage to claddings and investigates the damage potential of a cyclone as a function of all the relevant cyclone parameters, based on which it attempts to refine the current scale of cyclone intensity categories.

Prospects for studying how high-intensity compression waves cause damage in human blast injuries

Since World War I, explosions have accounted for over 70% of all injuries in conflict. With the development of improved personnel protection of the torso, improved medical care and faster aeromedical evacuation, casualties are surviving with more severe injuries to the extremities. Understanding the processes involved in the transfer of blast-induced shock waves through biological tissues is essential for supporting efforts aimed at mitigating and treating blast injury. Given the inherent heterogeneities in the human body, we argue that studying these processes demands a highly integrated approach requiring expertise in shock physics, biomechanics and fundamental biological processes. This multidisciplinary systems approach enables one to develop the experimental framework for investigating the material properties of human tissues that are subjected to high compression waves in blast conditions and the fundamental cellular processes altered by this type of stimuli. Ultimately, we hope to use the information gained from these studies in translational research aimed at developing improved protection for those at risk and improved clinical outcomes for those who have been injured from a blast wave.

Characterization of commercial double-walled carbon nanotube material : composition, structure, and heat capacity

A purified commercial double-walled carbon nanotube (DWCNT) sample was investigated by transmission electron microscopy (TEM), thermogravimetry (TG), and Raman spectroscopy. Moreover, the heat capacity of the DWCNT sample was determined by temperature-modulated differential scanning calorimetry in the range of temperature between -50 and 290 °C. The main thermo-oxidation characterized by TG occurred at 474 °C with the loss of 90 wt% of the sample. Thermo-oxidation of the sample was also investigated by high-resolution TG, which indicated that a fraction rich in carbon nanotube represents more than 80 wt% of the material. Other carbonaceous fractions rich in amorphous coating and graphitic particles were identified by the deconvolution procedure applied to the derivative of TG curve. Complementary structural data were provided by TEM and Raman studies. The information obtained allows the optimization of composites based on this nanomaterial with reliable characteristics.

Report : school survey to collect data on material performance

A survey of a number of schools in a number of different climates was carried out to determine the condition of building components of interest in the project. Schools in Melbourne, the Victorian Surf Coast, Brisbane, Townsville and the Sunshine Coast were inspected. A rating system was devised to categorise the components and the results collated in tables. Analysis of the data (where sufficient examples permitted) resulted in formulae to predict the service of the components and a database was derived.

Data mining on prices of highway project main material based on WEB

The management of main material prices of provincial highway project quota has problems of lag and blindness. Framework of provincial highway project quota data MIS and main material price data warehouse were established based on WEB firstly. Then concrete processes of provincial highway project main material prices were brought forward based on BP neural network algorithmic. After that standard BP algorithmic, additional momentum modify BP network algorithmic, self-adaptive study speed improved BP network algorithmic were compared in predicting highway project main prices. The result indicated that it is feasible to predict highway main material prices using BP NN, and using self-adaptive study speed improved BP network algorithmic is the relatively best one.