Scaling Analysis of Solidification of Liquid Aluminum Alloy Flowing on Cooling Slope

Among all methods of metal alloy slurry preparation, the cooling slope method is the simplest in terms of design and process control. The method involves pouring of the melt from top, down an oblique and channel shaped plate cooled from bottom by counter flowing water. The melt, while flowing down, partially solidifies and forms columnar dendrites on plate wall. These dendrites are broken into equiaxed grains and are washed away with melt. The melt, together with the equiaxed grains, forms semisolid slurry collected at the slope exit and cast into billets having non-dendritic microstructure. The final microstructure depends on several process parameters such as slope angle, slope length, pouring superheat, and cooling rate. The present work involves scaling analysis of conservation equations of momentum, energy and species for the melt flow down a cooling slope. The main purpose of the scaling analysis is to obtain a physical insight into the role and relative importance of each parameter in influencing the final microstructure. For assessing the scaling analysis, the trends predicted by scaling are compared against corresponding numerical results using an enthalpy based solidification model with incorporation of solid phase movement.

Bubble size measurement and error analysis in a gas liquid ejector

Bubble size in a gas liquid ejector has been measured using the image technique and analysed for estimation of Sauter mean diameter. The individual bubble diameter is estimated by considering the two dimensional contour of the ellipse, for the actual three dimensional ellipsoid in the system by equating the volume of the ellipsoid to that of the sphere. It is observed that the bubbles are of oblate and prolate shaped ellipsoid in this air water system. The bubble diameter is calculated based on this concept and the Sauter mean diameter is estimated. The error between these considerations is reported. The bubble size at different locations from the nozzle of the ejector is presented along with their percentage error which is around 18%.

Synthesis of zero valent iron nanoparticles and application to removal of arsenic(III) and arsenic(V) from water

Recently nano scale zero valent iron particles (nZVI) have been considered as smart adsorbent for environmental and groundwater remediation. Although several synthetic methods are available for the preparation of nZVI, air stable nZVI are not available for remediation works. Further, challenges demand synthesis of nZVI without stabilizers and capping agents. A modified methodology for the synthesis of air stable nZVI has been developed without any capping agents and characterized by powder X-Ray Diffraction (XRD), Scanning Electron Microscopy Energy-dispersive X-Ray (SEM-EDS), Transmission Electron Microscopy (TEM) and X-Ray Photoelectron Spectroscopy (XPS). The results of the present study suggest that the synthetic nZVI are air-stable over a period of one year and consists of particles of 30-40 nm in diameter. Although a layer of less than 3 am thick oxide/hydroxide is observed by TEM and XPS, it appears to be due to oxidation of outer surface during analysis. Adsorption study has shown that the synthetic nZVI are more effective adsorbent than the commercial nZVI and can remove simultaneously arsenite As-III] and arsenate As-V] from water without prior reduction of As-V to As-III. The removal process is adsorptive rather than precipitative and the removal of As-III is greater than that of As-V.

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

Low temperature CO oxidation and water gas shift reaction over Pt/Pd substituted in Fe/TiO2 catalysts

We demonstrate the activity of Ti0.84Pt0.01Fe0.15O2-delta and Ti0.73Pd0.02Fe0.25O2-delta catalysts towards the CO oxidation and water gas shift (VMS) reaction. Both the catalysts were synthesized in the nano crystalline form by a low temperature sonochemical method and characterized by different techniques such as XRD, FT-Raman, TEM, FT-IR, XPS and BET surface analyzer. H-2-TPR results corroborate the intimate contact between noble metal and Fe ions in the both catalysts that facilitates the reducibility of the support. In the absence of feed CO2 and H-2, nearly 100% conversion of CO to CO2 with 100% H-2 selectivity was observed at 300 degrees C and 260 degrees C respectively, for Ti0.84Pt0.01Fe0.15O2-delta and Ti0.73Pd0.02Fe0.25O2-delta catalyst. However, the catalytic performance of Ti0.73Pd0.02Fe0.25O2-delta deteriorates in the presence of feed CO2 and H-2. The change in the support reducibility is the primary reason for the significant increase in the activity for CO oxidation and WGS reaction. The effect of Fe addition was more significant in Ti0.73Pd0.02Fe0.25O2-delta than Ti0.84Pt0.01Fe0.15O2-delta. Based on the spectroscopic evidences and surface phenomena, a hybrid reaction scheme utilizing both surface hydroxyl groups and the lattice oxygen was hypothesized over these catalysts for WGS reaction. The mechanisms based on the formate and redox pathway were used to fit the ldnetic data. The analysis of experimental data shows the redox mechanism is the dominant pathway over these catalysts. Copyright (C) 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Water treatment potential in relation to phytoplankton dynamics in tropical sewage-fed urban water bodies

Urban water bodies frequently receive untreated sewage and water levels in such water bodies are maintained by daily inputs of sewage. They function as “variable-zone” anaerobic-aerobic lagoons suffering several macrophyte, biotic and abiotic stresses. We have studied two such lakes in Bangalore (Bellandur-360 ha and Varthur-220 ha) to understand whether such an occurrence could be made beneficial (maintaining water levels as well as treatment). Such hypertrophic water body receives sewage at 180-250mg/L and is discharged at 25-80mg/L COD/BOD in different seasons. In an earlier study we reported macrophyte altering the purification function of the water body. In this paper we studied the impact of phytoplankton dynamics and macrophyte cover on the functions such as organic load removal. Algal community analysis, algal biomass, macrophyte cover, water quality, nutrient status was studied seasonally during 2009-2010. Oxygen deficiency and sometimes anoxia, recorded from surface samples resulted in high quantities of NH4+-N (30-40mg/L) and phosphate (0.5-4mg/L)-characteristics of anoxic hypertrophic urban lakes. The productiveness favoured high phytoplanktonic community characterized by small cells (<10μm; Chlorella sp. - highest numbers). The lake could be clearly demarcated into an initial anaerobic zone (40% area), a facultative zone (20%) and an aerobic zone (40%) based on redox values and GIS/bathymetry. During summer the lake is covered by floating macrophytes converting the lake into an anoxic/anaerobic water pool subduing the water purification function as well as aesthetics. When macrophytes are controlled such sewage fed water bodies can be used for treating urban wastewater while also maintaining water sustainability in these semi-arid ecosystems. This paper reports the community dynamics of phytoplankton, their function and competition with macrophytes.

Pseudo-Static and Pseudo-Dynamic Stability Analysis of Tailings Dam Under Seismic Conditions

In this paper the seismic slope stability analyses are performed for a typical section of 44 m high water retention type tailings earthen dam located in the eastern part of India, using both the conventional pseudo-static and recent pseudo-dynamic methods. The tailings earthen dam is analyzed for different upstream conditions of reservoir like filled up with compacted and non-compacted dumped waste materials with different water levels of the pond tailings portion. Phreatic surface is generated using seepage analysis in geotechnical software SEEP/W and that same is used in the pseudo-static and pseudo-dynamic analyses to make the approach more realistic. The minimum values of factor of safety using pseudo-static and pseudo-dynamic method are obtained as 1.18 and 1.09 respectively for the chosen seismic zone in India. These values of factor of safety show clearly the demerits of conventional pseudo-static analysis compared to recent pseudo-dynamic analysis, where in addition to the seismic accelerations, duration, frequency of earthquake, body waves traveling during earthquake and amplification effects are considered.

Fuzzy data envelopment analysis for performance evaluation of an irrigation system

Sixteen irrigation subsystems of the Mahi Bajaj Sagar Project, Rajasthan, India, are evaluated and selection of the most suitable/best is made using data envelopment analysis (DEA) in both deterministic and fuzzy environments. Seven performance-related indicators, namely, land development works (LDW), timely supply of inputs (TSI), conjunctive use of water resources (CUW), participation of farmers (PF), environmental conservation (EC), economic impact (EI) and crop productivity (CPR) are considered. Of the seven, LDW, TSI, CUW, PF and EC are considered inputs, whereas CPR and EI are considered outputs for DEA modelling purposes. Spearman rank correlation coefficient values are also computed for various scenarios. It is concluded that DEA in both deterministic and fuzzy environments is useful for the present problem. However, the outcome of fuzzy DEA may be explored for further analysis due to its simple, effective data and discrimination handling procedure. It is inferred that the present study can be explored for similar situations with suitable modifications.

Ionomer based blend as water vapor barrier material for organic device encapsulation

Blends of poly (ethylene-co-methacrylic acid) (PEMA) and poly (vinyl alcohol-co-ethylene) (EVOH) were studied for encapsulating Schottky structured organic devices. A calcium degradation test was used to determine water vapor transmission rates and to determine the moisture barrier performance of neat and blend films. Moisture barrier analysis for the neat and blend compositions was discussed concerning the interactions in the blend, diffusivity of water molecules through the unit cell systems, and the occupiable free volumes available in the unit cells using molecular dynamics simulations. The experimental results of water vapor permeation were correlated with diffusion behavior predicted from molecular dynamics simulations results. The effectiveness of the blend as a suitable barrier material in increasing the lifetime of an encapsulated Schottky structured organic device was determined.

Solvation dynamics of tryptophan in water-dimethyl sulfoxide binary mixture: In search of molecular origin of composition dependent multiple anomalies

Experimental and simulation studies have uncovered at least two anomalous concentration regimes in water-dimethyl sulfoxide (DMSO) binary mixture whose precise origin has remained a subject of debate. In order to facilitate time domain experimental investigation of the dynamics of such binary mixtures, we explore strength or extent of influence of these anomalies in dipolar solvation dynamics by carrying out long molecular dynamics simulations over a wide range of DMSO concentration. The solvation time correlation function so calculated indeed displays strong composition dependent anomalies, reflected in pronounced non-exponential kinetics and non-monotonous composition dependence of the average solvation time constant. In particular, we find remarkable slow-down in the solvation dynamics around 10%-20% and 35%-50% mole percentage. We investigate microscopic origin of these two anomalies. The population distribution analyses of different structural morphology elucidate that these two slowing down are reflections of intriguing structural transformations in water-DMSO mixture. The structural transformations themselves can be explained in terms of a change in the relative coordination number of DMSO and water molecules, from 1DMSO:2H(2)O to 1H(2)O:1DMSO and 1H(2)O:2DMSO complex formation. Thus, while the emergence of first slow down (at 15% DMSO mole percentage) is due to the percolation among DMSO molecules supported by the water molecules (whose percolating network remains largely unaffected), the 2nd anomaly (centered on 40%-50%) is due to the formation of the network structure where the unit of 1DMSO:1H(2)O and 2DMSO:1H(2)O dominates to give rise to rich dynamical features. Through an analysis of partial solvation dynamics an interesting negative cross-correlation between water and DMSO is observed that makes an important contribution to relaxation at intermediate to longer times.

Remote sensing applications in water resources

With the introduction of the earth observing satellites, remote sensing has become an important tool in analyzing the Earth's surface characteristics, and hence in supplying valuable information necessary for the hydrologic analysis. Due to their capability to capture the spatial variations in the hydro-meteorological variables and frequent temporal resolution sufficient to represent the dynamics of the hydrologic processes, remote sensing techniques have significantly changed the water resources assessment and management methodologies. Remote sensing techniques have been widely used to delineate the surface water bodies, estimate meteorological variables like temperature and precipitation, estimate hydrological state variables like soil moisture and land surface characteristics, and to estimate fluxes such as evapotranspiration. Today, near-real time monitoring of flood, drought events, and irrigation management are possible with the help of high resolution satellite data. This paper gives a brief overview of the potential applications of remote sensing in water resources.

Relation Between the Diffusivity, Viscosity, and Ionic Radius of LiCl in Water, Methanol, and Ethylene Glycol: A Molecular Dynamics Simulation

A molecular dynamics (MD) investigation of LiCl in water, methanol, and ethylene glycol (EG) at 298 K is reported. Several; structural and dynamical properties of the ions as well as the solvent such as self-diffusivity, radial distribution functions, void and neck distributions, velocity autocorrelation functions, and mean residence times of solvent in the first solvation shell have been computed. The results show that the reciprocal relationship between the self-diffusivity of the ions and the viscosity is valid in almost all solvents with the exception of water. From an analysis of radial distribution functions and coordination numbers the nature of hydrogen bonding within the solvent and its influence on the void and neck distribution becomes evident. It is seen that the solvent solvent interaction is important in EG while solute solvent interactions dominate in water and methanol. From Voronoi tessellation, it is seen that the voids and necks within methanol are larger as compared to those within water or EG. On the basis of the void and neck distributions obtained from MD simulations and literature experimental data of limiting ion conductivity for various ions of different sizes we show that there is a relation between the void and neck radius on e one hand and dependence of conductivity on the ionic radius on the other. It is shown that the presence of large diameter voids and necks in methanol is responsible for maximum in limiting ion conductivity (lambda(0)) of TMA(+), while in water in EG, the maximum is seen for Rb+. In the case of monovalent anions, maximum in lambda(0) as a function ionic radius is seen for Br- in water EG but for the larger ClO4- ion in methanol. The relation between the void and neck distribution and the variation in lambda(0) with ionic radius arises via the Levitation effect which is discussed. These studies show the importance of the solvent structure and the associated void structure.

Spectral analysis of Cauvery river flows

A detalied study of the maonthly Convery river flows at the krishna raja sagara (KRS) reservoir is carried out by using the techniques of spectral analysis. The correlogram and power spectrum ate platted and used to identify the peridiocities inherent in the monthly inflows. The statistical significance of these periodicities is tested. Apart from the periodiocities at 12 months and 6 months, a significant of periodicity of 4 month was also observed in the monthly inflows. The analysis prepares ground for developing an appropriate stochastic model for the item series of the monthly flows.

Regional impacts of climate change on irrigation water demands

This paper presents an approach to model the expected impacts of climate change on irrigation water demand in a reservoir command area. A statistical downscaling model and an evapotranspiration model are used with a general circulation model (GCM) output to predict the anticipated change in the monthly irrigation water requirement of a crop. Specifically, we quantify the likely changes in irrigation water demands at a location in the command area, as a response to the projected changes in precipitation and evapotranspiration at that location. Statistical downscaling with a canonical correlation analysis is carried out to develop the future scenarios of meteorological variables (rainfall, relative humidity (RH), wind speed (U-2), radiation, maximum (Tmax) and minimum (Tmin) temperatures) starting with simulations provided by a GCM for a specified emission scenario. The medium resolution Model for Interdisciplinary Research on Climate GCM is used with the A1B scenario, to assess the likely changes in irrigation demands for paddy, sugarcane, permanent garden and semidry crops over the command area of Bhadra reservoir, India. Results from the downscaling model suggest that the monthly rainfall is likely to increase in the reservoir command area. RH, Tmax and Tmin are also projected to increase with small changes in U-2. Consequently, the reference evapotranspiration, modeled by the Penman-Monteith equation, is predicted to increase. The irrigation requirements are assessed on monthly scale at nine selected locations encompassing the Bhadra reservoir command area. The irrigation requirements are projected to increase, in most cases, suggesting that the effect of projected increase in rainfall on the irrigation demands is offset by the effect due to projected increase/change in other meteorological variables (viz., Tmax and Tmin, solar radiation, RH and U-2). The irrigation demand assessment study carried out at a river basin will be useful for future irrigation management systems. Copyright (c) 2012 John Wiley & Sons, Ltd.