Cooperative Research Centre

About: Cooperative Research Centre is a based out in . It is known for research contribution in the topics: Population & Sea ice. The organization has 7633 authors who have published 8607 publications receiving 429721 citations.

Thermally enhanced machining of hard-to-machine materials: a review

Abstract: Thermally enhanced machining uses external heat sources to heat and soften the workpiece locally in front of the cutting tool. The temperature rise at the shear zone reduces the yield strength and work hardening of the workpiece, which make the plastic deformation of hard-to-machine materials easier during machining. This review summarizes the up-to-date progress and benefits of thermally enhanced machining (with a focus on laser and plasma assistance) of ceramics, metals and metal matrix composites. It covers the integration of the external heat source with cutting tools, analysis of temperature distribution around the cutting region, material removal mechanisms, tool wear mechanisms and the improvement in machinability of various engineering materials by the assistance of external heat source.

Understanding variability in winegrape production systems

Abstract: Spatial variability in winegrape yield was studied over several vintages in blocks planted to Cabernet Sauvignon, Merlot and Ruby Cabernet in the Coonawarra, Clare Valley and Sunraysia regions of Australia using new yield monitoring technology, a differentially corrected global positioning system (GPS), a geographical information system and some simple methods of spatial analysis. In any given year, yield was highly variable and typically of the order of 10 fold (i.e. 2 to 20 t/ha). However, through the use of k-means clustering and a method based on assessment of the probability of achieving yield targets relative to the mean annual block yield, temporal stability in the patterns of yield variation was demonstrated, even though there were substantial year to year differences in mean annual yield in these blocks. The methods used to demonstrate temporal stability in the patterns of yield variation also promote identification of zones of characteristic performance within variable vineyard blocks. Of significance in this work was the finding that, whilst k-means clustering is the more statistically robust of the two methods used, the ability to incorporate expert knowledge into the yield target method enhances the ability of the manager to accommodate the effects of abnormal events (e.g. an unusually cold flowering period) in the zone identification process. Targeted harvesting of different zones, followed by comparison between commercial lots of wine, provided indication that wine characteristics vary from zone to zone. However, the ranking of wine scores for the various zones changed between seasons. Our results have important implications for the adoption of Precision Viticulture. In particular, they support the introduction of a system of zonal vineyard management. Thus, rather than being managed uniformly, individual blocks can be split into zones in which the management of both inputs to, and outputs from the production system can be applied differentially.

Assessing recent trends in high-latitude Southern Hemisphere surface climate

Abstract: Understanding the causes of recent climatic trends and variability in the high-latitude Southern Hemisphere is hampered by a short instrumental record. Here, we analyse recent atmosphere, surface ocean and sea-ice observations in this region and assess their trends in the context of palaeoclimate records and climate model simulations. Over the 36-year satellite era, significant linear trends in annual mean sea-ice extent, surface temperature and sea-level pressure are superimposed on large interannual to decadal variability. Most observed trends, however, are not unusual when compared with Antarctic palaeoclimate records of the past two centuries. With the exception of the positive trend in the Southern Annular Mode, climate model simulations that include anthropogenic forcing are not compatible with the observed trends. This suggests that natural variability overwhelms the forced response in the observations, but the models may not fully represent this natural variability or may overestimate the magnitude of the forced response.