Engineering closure of an open pit gold operation in a semi-arid climate

Along with material characteristics and geometry, the climate in which a mine is located can have a dramatic effect on the appropriate options for rehabilitation. The paper outlines the setting, mining, milling and waste disposal at Kidston Gold Mine's open pit operations in the semi-arid climate of North Queensland, Australia, before focusing on the engineering aspects of the rehabilitation of Kidston. The mine took a holistic and proactive approach to rehabilitation, and was prepared to demonstrate a number of innovative approaches, which are described in the paper. Engineering issues that had to be addressed included the geotechnical stability and deformation of waste rock dumps, including a 240 m high in-pit dump: the construction and performance monitoring of a “store and release” cover over potentially acid forming mineralised waste rock; erosion from the side slopes of the waste rock dumps; the in-pit co-disposal of waste rock and thickened tailings; the geotechnical stability of the tailings dam wall; the potential for erosion of bare tailings; the water balance of the tailings dam; direct revegetation of the tailings; and the pit hydrology. The rehabilitation of the mine represents an important benchmark in mine site rehabilitation best practice, from which lessons applicable worldwide can be shared.

Monitoring hotel performance

There is a pressing need to address productivity analysis in the hospitality industry if hotels are to exist as sustainable business entities in rapidly maturing markets. Unfortunately, productivity ratios commonly used by managers are narrowly defined. This study illustrates data envelopment analysis of cross-sectional data that benchmark hotels on observed best performances. Data envelopment analysis enables management to integrate unlike multiple inputs and outputs to make simultaneous comparisons. Findings from the cross-sectional data suggest that some of the hotels have the potential to reduce number of beds and number of part-time staff while increasing revenue.

Analysis of the effect of transverse modes on free-space optical interconnect performance

Vertical-cavity surface-emitting lasers (VCSELs) and microlenses can be used to implement free space optical interconnects (FSOIs) which do not suffer from the bandwidth limitations inherent in metallic interconnects. A comprehensive link equation describing the effects of both optical and electrical noise is introduced. We have evaluated FSOI performance by examining the following metrics: the space-bandwidth product (SBP), describing the density of channels and aggregate bandwidth that can be achieved, and the carrier-to-noise ratio (CNR), which represents the relative strength of the carrier signal. The mode expansion method (MEM) was used to account for the primary cause of optical noise: laser beam diffraction. While the literature commonly assumes an ideal single-mode laser beam, we consider the experimentally determined multimodal structure of a VCSEL beam in our calculations. It was found that maximum achievable interconnect length and density for a given CNR was significantly reduced when the higher order transverse modes were present in Simulations. However, the Simulations demonstrate that free-space optical interconnects are still a suitable solution for the communications bottleneck, despite the adverse effects introduced by transverse modes.

Investigation of the Effect of Array Geometry on the Performance of Free-Space Optical Interconnects

The effect of transmitter and receiver array configurations on the stray-light and diffraction-caused crosstalk in free-space optical interconnects was investigated. The optical system simulation software (Code V) is used to simulate both the stray-light and diffraction-caused crosstalk. Experimentally measured, spectrally-resolved, near-field images of VCSEL higher order modes were used as extended sources in our simulation model. In addition, we have included the electrical and optical noise in our analysis to give more accurate overall performance of the FSOI system. Our results show that by changing the square lattice geometry to a hexagonal configuration, we obtain an overall signal-to-noise ratio improvement of 3 dB. Furthermore, system density is increased by up to 4 channels/mm2.

Determining forest structural attributes using an inverted geometric-optical model in mixed eucalypt forests, Southeast Queensland, Australia

The Montreal Process indicators are intended to provide a common framework for assessing and reviewing progress toward sustainable forest management. The potential of a combined geometrical-optical/spectral mixture analysis model was assessed for mapping the Montreal Process age class and successional age indicators at a regional scale using Landsat Thematic data. The project location is an area of eucalyptus forest in Emu Creek State Forest, Southeast Queensland, Australia. A quantitative model relating the spectral reflectance of a forest to the illumination geometry, slope, and aspect of the terrain surface and the size, shape, and density, and canopy size. Inversion of this model necessitated the use of spectral mixture analysis to recover subpixel information on the fractional extent of ground scene elements (such as sunlit canopy, shaded canopy, sunlit background, and shaded background). Results obtained fron a sensitivity analysis allowed improved allocation of resources to maximize the predictive accuracy of the model. It was found that modeled estimates of crown cover projection, canopy size, and tree densities had significant agreement with field and air photo-interpreted estimates. However, the accuracy of the successional stage classification was limited. The results obtained highlight the potential for future integration of high and moderate spatial resolution-imaging sensors for monitoring forest structure and condition. (C) Elsevier Science Inc., 2000.

Quantification of free mycophenolic acid by high-performance liquid chromatography-atmospheric pressure chemical ionisation tandem mass spectrometry

To facilitate the investigation of free mycophenolic acid concentrations we developed a high-performance liquid chromatography tandem mass spectrometry method using indomethacin as an internal standard. Free drug was isolated from plasma samples (500 mul) using ultrafiltration, The analytes were extracted from the ultrafiltrate (200 mul) using C-18 solid-phase extraction. Detection was by selected reactant monitoring of mycophenolic acid (m/z 318.9-->190.9) and the internal standard (m/z 356.0-->297.1) with an atmospheric pressure chemical ionisation interface. The total chromatographic analysis time was 12 min. The method was found to be linear over the range investigated, 2.5-200 mug/l (r>0.990, n=6). The relative recovery of the method for the control samples studied (7.5, 40.0 and 150 mug/l) ranged from 95 to 104%. The imprecision of the method, expressed in terms of intra- and inter-day coefficients of variation, was

Simulated-annealing-based genetic algorithm for modeling the optical constants of solids

We propose a simulated-annealing-based genetic algorithm for solving model parameter estimation problems. The algorithm incorporates advantages of both genetic algorithms and simulated annealing. Tests on computer-generated synthetic data that closely resemble optical constants of a metal were performed to compare the efficiency of plain genetic algorithms against the simulated-annealing-based genetic algorithms. These tests assess the ability of the algorithms to and the global minimum and the accuracy of values obtained for model parameters. Finally, the algorithm with the best performance is used to fit the model dielectric function to data for platinum and aluminum. (C) 1997 Optical Society of America.

Population pharmacokinetics of perhexiline from very sparse, routine monitoring data

Using NONMEM, the population pharmacokinetics of perhexiline were studied in 88 patients (34 F, 54 M) who were being treated for refractory angina. Their mean +/- SD (range) age was 75 +/- 9.9 years (46-92), and the length of perhexiline treatment was 56 +/- 77 weeks (0.3-416). The sampling time after a dose was 14.1 +/- 21.4 hours (0.5-200), and the perhexiline plasma concentrations were 0.39 +/- 0.32 mg/L (0.03-1.56). A one-compartment model with first-order absorption was fitted to the data using the first-order (FO) approximation. The best model contained 2 subpopulations (obtained via the $MIXTURE subroutine) of 77 subjects (subgroup A) and 11 subjects (subgroup B) that had typical values for clearance (CL/F) of 21.8 L/h and 2.06 L/h, respectively. The volumes of distribution (V/F) were 1470 L and 260 L, respectively, which suggested a reduction in presystemic metabolism in subgroup B. The interindividual variability (CV%) was modeled logarithmically and for CL/F ranged from 69.1% (subgroup A) to 86.3% (subgroup B). The interindividual variability in V/F was 111%. The residual variability unexplained by the population model was 28.2%. These results confirm and extend the existing pharmacokinetic data on perhexiline, especially the bimodal distribution of CL/F manifested via an inherited deficiency in hepatic and extrahepatic CYP2D6 activity.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.