Volume Change behaviour in Calcitic Soil influenced with Sulphuric Acid using Artificial Neural Networks

This paper elucidates the methodology of applying artificial neural network model (ANNM) to predict the percent swell of calcitic soil in sulphuric acid solutions, a complex phenomenon involving many parameters. Swell data required for modelling is experimentally obtained using conventional oedometer tests under nominal surcharge. The phases in ANN include optimal design of architecture, operation and training of architecture. The designed optimal neural model (3-5-1) is a fully connected three layer feed forward network with symmetric sigmoid activation function and trained by the back propagation algorithm to minimize a quadratic error criterion.The used model requires parameters such as duration of interaction, calcite mineral content and acid concentration for prediction of swell. The observed strong correlation coefficient (R2 = 0.9979) between the values determined by the experiment and predicted using the developed model demonstrates that the network can provide answers to complex problems in geotechnical engineering.

Growth and attachment of Thiobacillus ferrooxidans during sulfide mineral leaching

The growth of Thiobacillus ferrooxidans, their attachment to sulfide minerals and detachment during bacterial leaching are discussed in this paper. Growth of the bacteria has been measured by cell count of the supernatants of the mineral suspensions while attachment to minerals and detachment were measured by periodic protein estimations for both the solid and liquid phases, Even in the absence of the nutrients, bacterial growth occurs and increases the available cell population during leaching; such growth was greater in sphalerite suspensions than in galena suspensions, The bacterial attachment studies suggest that more cells are attached onto galena mineral surface than to sphalerite surface. The mechanisms of bacterial attachment and detachment are discussed.

Implementation of Art1 and Art2 Artificial Neural Networks on Ring and Mesh Architectures

The Artificial Neural Networks (ANNs) are being used to solve a variety of problems in pattern recognition, robotic control, VLSI CAD and other areas. In most of these applications, a speedy response from the ANNs is imperative. However, ANNs comprise a large number of artificial neurons, and a massive interconnection network among them. Hence, implementation of these ANNs involves execution of computer-intensive operations. The usage of multiprocessor systems therefore becomes necessary. In this article, we have presented the implementation of ART1 and ART2 ANNs on ring and mesh architectures. The overall system design and implementation aspects are presented. The performance of the algorithm on ring, 2-dimensional mesh and n-dimensional mesh topologies is presented. The parallel algorithm presented for implementation of ART1 is not specific to any particular architecture. The parallel algorithm for ARTE is more suitable for a ring architecture.

Estimation of mineral-adhered biomass of Thiobacillusferrooxidans by protein assay-some problems and remedies

Enumeration of adhered cells of Thiobacillus ferrooxidans on sulphide minerals through protein assay poses problems due to interference from dissolved mineral constituents. The manner in which sulphide minerals such as pyrite, chalcopyrite, sphalerite, arsenopyrite and pyrrhotite interfere with bacterial protein estimation is demonstrated. Such interferences can be minimised either through dilution or addition of H2O2 to the filtrate after hot alkaline digestion of the biotreated mineral samples.

Buoyant Jet Discharges into Finite Ambient Waters

The paper presents the results of an experimental study regarding the effect of the lateral dimension of the receiving water on the spreading, mixing, and temperature decay of a horizontal buoyant surface jet. The widths of the ambient water in the experiments have been 240, 120, 90 and 60 times the diameter of the jet nozzle. Based on the experimental data, correlations are carried out and empirical equations for prediction of jet width, thickness in vertical direction and longitudinal temperature decay are obtained. The available data of earlier investigators are included to obtain generalized equations for the spreading and temperature decay. Similarity of temperature profiles in the lateral and vertical directions is observed. The longitudinal temperature decay is found to vary inversely with distance in the flow direction and ¼th power of the densimetric Froude number.

Application of Artificial Viscosity in Establishing Supercritical Solutions to the Transonic Integra

The nonlinear singular integral equation of transonic flow is examined in the free-stream Mach number range where only solutions with shocks are known to exist. It is shown that, by the addition of an artificial viscosity term to the integral equation, even the direct iterative scheme, with the linear solution as the initial iterate, leads to convergence. Detailed tables indicating how the solution varies with changes in the parameters of the artificial viscosity term are also given. In the best cases (when the artificial viscosity is smallest), the solutions compare well with known results, their characteristic feature being the representation of the shock by steep gradients rather than by abrupt discontinuities. However, 'sharp-shock solutions' have also been obtained by the implementation of a quadratic iterative scheme with the 'artificial viscosity solution' as the initial iterate; the converged solution with a sharp shock is obtained with only a few more iterates. Finally, a review is given of various shock-capturing and shock-fitting schemes for the transonic flow equations in general, and for the transonic integral equation in particular, frequent comparisons being made with the approach of this paper.

Lighting the way: Towards reducing misorientation of olive ridley hatchlings due to artificial lighting at Rushikulya, India

Sea-finding behavior in sea turtle hatchlings is modified by the visual cues provided by artificial beach front lighting. The consequent landward movement of hatchlings in response to coastal electric lighting reduces their survival rates. We assessed the potential impact of coastal lighting at Rushikulya, an important mass nesting site of the olive ridley sea turtle (Lepidochelys olivacea) in the Indian Ocean region. We examined the response of hatchlings to light characteristics in an experimental setup, as well as to the existing lighting regimes along the beach, using arena trials. Previous studies on other species indicate preferential orientation towards low wavelength and high intensity light. Our study confirms these preferences among hatchlings from the Indian Ocean population of olive ridleys. In addition we also found that wavelength and intensity could have an interactive effect upon hatchling orientation. Hatchlings at the study site respond both to visible point sources of light and to sheer glows of light. Though beach plantations of introduced Casuarina equisetifolia are generally considered to have negative impacts on sea turtle nesting beaches, we found that they acted as an effective light barrier when planted about 50 m away from the high tide line. We developed a model of the expected impact of artificial lighting on hatchling orientation during mass hatching events of previous years, and predict as much as 50% misorientation in some years. We also developed a map representing the misorientation of hatchlings due to artificial lighting based on arena trials in different regions of the beach. The results of the study helped identify focal areas for light management on the beach, which could be critical for the survival of this population.

Role of cell attachment in leaching of chalcopyrite mineral by Thiobacillus ferrooxidans

Experiments on the leaching of copper from chalcopyrite mineral by the bacterium Thiobacillus ferrooxidans show that, in the presence of adequate amounts of sulphide, iron-grown bacteria preferentially oxidise sulphur in the ore (through direct attachment) rather than ferrous sulphate in solution. At 20% pulp density, the leaching initially takes place by a predominantly direct mechanism. The cell density in the liquid phase increases, but the Fe2+ is not oxidised. However, in the later stages when less solid substrate is available and the cell density becomes very high, the bacteria start oxidising Fe2+ in the liquid phase, thus contributing to the indirect mechanism of leaching. Contrary to expectations, the rate of leaching increased with increasing particle size in spite of the decreasing specific surface area. This has been found to be due to increasing attachment efficiency with increase in particle size.

Application of artificial intelligence for the assessment of the status of power transformers

The Dissolved Gas Analysis (DGA) a non destructive test procedure, has been in vogue for a long time now, for assessing the status of power and related transformers in service. An early indication of likely internal faults that may exist in Transformers has been seen to be revealed, to a reasonable degree of accuracy by the DGA. The data acquisition and subsequent analysis needs an expert in the concerned area to accurately assess the condition of the equipment. Since the presence of the expert is not always guaranteed, it is incumbent on the part of the power utilities to requisition a well planned and reliable artificial expert system to replace, at least in part, an expert. This paper presents the application of Ordered Ant Mner (OAM) classifier for the prediction of involved fault. Secondly, the paper also attempts to estimate the remaining life of the power transformer as an extension to the elapsed life estimation method suggested in the literature.

Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are considered as the classification criteria for grouping. The optimal number of groups is determined as 14 based on the Davies-Bouldin index approach. It is observed that the FCA approach performed better than the other two methodologies for the present study.

Investigation of true remnant polarization response in heterostructured artificial biferroics

Epitaxial bilayered thin films composed of ferromagnetic La0.6Sr0.4MnO3 and ferroelectric 0.7Pb (Mg1/3Nb2/3)O3-0.3(PbTiO3) were fabricated on LaAlO3 (100) substrates by pulsed laser ablation. Ferroelectric, ferromagnetic and magneto-dielectric characterizations performed earlier indicated the possible existence of strain-mediated magneto-electric coupling in these biferroic heterostructures. In order to investigate their true remnant polarization characteristics, usable in devices, room-temperature polarization versus electric field, positive-up negative-down (PUND) pulse polarization studies and remnant hysteresis measurements were carried out. The PUND and remnant hysteresis measurements revealed the significant contribution of the non-remnant component in the observed polarization hysteresis response of these heterostructures. (C) 2010 Published by Elsevier Ltd

Microbially Induced Mineral Beneficiation

The divergent role of microbes in the field of mineral processing starting from mining and beneficiation to efficient waste disposal has been well recognized now. The roles of various microorganisms and bioreagents in the beneficiation of minerals are illustrated in this paper. Various types of microorganisms useful in bringing about selective flotation and flocculation of various oxide and sulfide minerals are illustrated. Interfacial phenomena governing microbe-mineral interactions are discussed with reference to bacterial cell wall architecture, cell surface hydrophobicity, electrokinetic data, and adsorption behavior on various minerals. Applications of microbially induced mineral beneficiation are demonstrated with respect to beneficiation of iron ores, bauxite, limestone, and complex multimetal sulfides.

Adhesion of Acidithiobacillus ferrooxidans to mineral surfaces

Direct contact mechanism in bioleaching implies prior mineral adhesion of Acidithiobacillus ferrooxidans and subsequent enzymatic attack.Prior bacterial adaptation to sulfide mineral substrates influences bacterial ferrous ion oxidation rates. It is highly beneficial to understand major biooxidation mechanisms with reference to solution- and mineral-grown cells in order to optimize bioleaching reactions. For A. ferrooxidans grown in the presence of solid substrates such as sulfur, pyrite and chalcopyrite, bacterial adhesion is required for its enzymatic machinery to come into close contact for mineral dissolution.But when grown in solution substrate such as ferrous ions and thiosulfate, such an adhesion machinery is not required for substrate utilization. Proteinaceous compounds were observed on the surface of sulfur-grown cells. Such an induction of relatively hydrophobic proteins and down regulation of exposed polysaccharides leads to changes in cell surface chemistry. Sulfur-grown and pyrite- and chalcopyrite-grown bacterial cells were found to be more efficient in the bioleaching of chalcopyrite than those grown in the presence of ferrous ions and thiosulfate. (C) 2010 Elsevier B.V. All rights reserved.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.