Influence of charge size distribution on net-power draw of tumbling mill based on DEM modelling

Modelling and optimization of the power draw of large SAG/AG mills is important due to the large power draw which modern mills require (5-10 MW). The cost of grinding is the single biggest cost within the entire process of mineral extraction. Traditionally, modelling of the mill power draw has been done using empirical models. Although these models are reliable, they cannot model mills and operating conditions which are not within the model database boundaries. Also, due to its static nature, the impact of the changing conditions within the mill on the power draw cannot be determined using such models. Despite advances in computing power, discrete element method (DEM) modelling of large mills with many thousands of particles could be a time consuming task. The speed of computation is determined principally by two parameters: number of particles involved and material properties. The computational time step is determined by the size of the smallest particle present in the model and material properties (stiffness). In the case of small particles, the computational time step will be short, whilst in the case of large particles; the computation time step will be larger. Hence, from the point of view of time required for modelling (which usually corresponds to time required for 3-4 mill revolutions), it will be advantageous that the smallest particles in the model are not unnecessarily too small. The objective of this work is to compare the net power draw of the mill whose charge is characterised by different size distributions, while preserving the constant mass of the charge and mill speed. (C) 2004 Elsevier Ltd. All rights reserved.

Does high intensity resistance training maintain bone mass during moderate weight loss in older overweight adults with type 2 diabetes

The aim was to investigate whether the addition of supervised high intensity progressive resistance training to a moderate weight loss program (RT+WLoss) could maintain bone mineral density (BMD) and lean mass compared to moderate weight loss (WLoss) alone in older overweight adults with type 2 diabetes. We also investigated whether any benefits derived from a supervised RT program could be sustained through an additional home-based program. This was a 12-month trial in which 36 sedentary, overweight adults aged 60 to 80 years with type 2 diabetes were randomized to either a supervised gymnasium-based RT+WLoss or WLoss program for 6 months (phase 1). Thereafter, all participants completed an additional 6-month home-based training without further dietary modification (phase 2). Total body and regional BMD and bone mineral content (BMC), fat mass (FM) and lean mass (LM) were assessed by DXA every 6 months. Diet, muscle strength (1-RM) and serum total testosterone, estradiol, SHBG, insulin and IGF-1 were measured every 3 months. No between group differences were detected for changes in any of the hormonal parameters at any measurement point. In phase 1, after 6 months of gymnasium-based training, weight and FM decreased similarly in both groups (P < 0.01), but LM tended to increase in the RT+WLoss (n=16) relative to the WLoss (n = 13) group [net difference (95% CI), 1.8% (0.2, 3.5), P < 0.05]. Total body BMD and BMC remained unchanged in the RT+WLoss group, but decreased by 0.9 and 1.5%, respectively, in the WLoss group (interaction, P < 0.05). Similar, though non-significant, changes were detected at the femoral neck and lumbar spine (L2-L4). In phase 2, after a further 6 months of home-based training, weight and FM increased significantly in both the RT+WLoss (n = 14) and WLoss (n = 12) group, but there were no significant changes in LM or total body or regional BMD or BMC in either group from 6 to 12 months. These results indicate that in older, overweight adults with type 2 diabetes, dietary modification should be combined with progressive resistance training to optimize the effects on body composition without having a negative effect on bone health.