Removal of lead(II) by adsorption using treated granular activated carbon: batch and column studies

In the present study, a deeper understanding of adsorption behavior of Pb(II) from aqueous systems onto activated carbon and treated activated carbon has been attempted via static and column mode studies under various conditions. It probes mainly two adsorbents that is, activated carbon (AC) and modified activated carbon (AC-S). Characterization of both the adsorbents was one of the key focal areas of the present study. This has shown a clear change or demarcation in the various physical and chemical properties of the modified adsorbent from its precursor activated carbon. Both the adsorbents are subjected to static mode adsorption studies and then after a comparison based on isotherm analysis; more efficient adsorbent is screened for column mode adsorption studies. The lead removal increased for sample of treated carbon. The extent of Pb(II) removal was found to be higher in the treated activated carbon. The aim of carrying out the continuous-flow studies was to assess the effect of various process variables, viz., of bed height, hydraulic loading rate and initial feed concentration on breakthrough time and adsorption capacity. This has helped in ascertaining the practical applicability of the adsorbent. Breakthrough curves were plotted for the adsorption of lead on the adsorbent using continuous-flow column operation by varying different operating parameters like hydraulic loading rate (3.0-10.5 m3/(hm2)), bed height (0.3-0.5 m) and feed concentrations (2.0-6.0 mg/l). At the end, an attempt has also been made to model the data generated from column studies using the empirical relationship based on Bohart-Adams model. This model has provided an objective framework to the subjective interpretation of the adsorption system and the model constant obtained here can be used to achieve the ultimate objective of our study that is, up scaling and designing of adsorption process at the pilot plant scale level. AC-S column regeneration using 0.5 and 1.0M concentration of HNO3 has been investigated. It has shown a regeneration efficiency of 52.0% with 0.5 M HNO3.     

Stress and Fracture Behavior of Monolithic Fuel Cell Tapes

This paper summarizes the stress and fracture analyses of a three-layer ceramic composite which is a fundamental building block for the monolithic solid oxide fuel tell currently being developed at Argonne National Laboratory. A small difference in the coefficients of thermal expansion of different layers can result in large stresses and cause cracking parallel to the plane of the layers. A simple fracture model for a three-layer composite has been developed. The cracking behavior predicted by the model is in reasonably good agreement with the fabrication experience to date.     

BIGM: A Biogeography Inspired Group Mobility Model for Mobile Ad Hoc Networks

This paper propounds a novel Biogeography Inspired Group Mobility model for Mobile Ad Hoc Networks (MANETs) based on the Biogeography Based Optimization (BBO) algorithm. BBO describes the migration behavior of species between the islands and how they become extinct and new species arise. Many mobility models present in the literature failed to realistically represent the movement of nodes within the group and migration of nodes from one group to another group. To address these issues, each group of nodes in the proposed mobility model follows the bird flocking rules; inspired from the movement of flock of birds. These nodes then migrate from one group to another group based on BBO approach, showing group mobility behavior among the group of nodes in MANETs which exhibit frequent group motion and network topology changes. The experimental results obtained through ns-2 simulator is compared with a Random Waypoint Mobility model and Reference Point Group Mobility model and evaluated their network performance under different routing protocols.     

Assessing compressive strengths of mortar and concrete from digital images by machine learning techniques

Compressive strength is the most important metric of concrete quality. Various nondestructive and semi-destructive tests can be used to evaluate the compressive strength of concrete. In the present study, a new image-based machine learning method is used to predict concrete compressive strength, including evaluation of six different models. These include support-vector machine model and various deep convolutional neural network models, namely AlexNet, GoogleNet, VGG19, ResNet, and Inception-ResNet-V2. In the present investigation, cement mortar samples were prepared using each of the cement:sand ratios of 1:3, 1:4, and 1:5, and using the water:cement ratios of 0.35 and 0.55. Cement concrete was prepared using the cement:sand:coarse aggregate ratios of 1:5:10, 1:3:6, 1:2:4, 1:1.5:3 and 1:1:2, using the water:cement ratio of 0.5 for all samples. The samples were cut, and several images of the cut surfaces were captured at various zoom levels using a digital microscope. All samples were then tested destructively for compressive strength. The images and corresponding compressive strength were then used to train machine learning models to allow them to predict compressive strength based upon the image data. The Inception-ResNet-V2 models exhibited the best predictions of compressive strength among the models tested. Overall, the present findings validated the use of machine learning models as an efficient means of estimating cement mortar and concrete compressive strengths based on digital microscopic images, as an alternative nondestructive/semi-destructive test method that could be applied at relatively less expense.     

A 10 nm MOS and its applications

Microsystem Technologies - A 10 nm Metal Oxide Semiconductor Field Effect Transistor (MOSFET) and Complementary Metal Oxide Semiconductor (CMOS) are presented in this paper. A channel...     

SDN assisted self organizing network architecture for multi-RAT networks and mobility prediction

Wireless Networks - Existing and future wireless networks are expected to have multiple Radio Access Technologies (RAT), primarily due to legacy reasons and introduction of newer technologies....     

Physiological cost of work under hot dry climates in Indian industries An analysis

The possibility of using pulse rate during work as a measure of the energy coat of that work, in lieu of the more cumbersome gas analysis techniques, has been examined in actual industrial environments for varied work and thermal loads. Three sets of data from some hot dry industries situated in different parts of India were analysed : (a) extreme levels ; (b) moderate levelB ; and (c) comparatively low levels of work and heat loads. Pulse rate (PR) measurements, in conjunction with body surface area (BSA) and corrected effective temperature (CET) were found to be significantly correlated with energy expenditure (EE) at both high and moderate levels (τ = 0-889 and 0-902, respectively); the predictive ability of the corresponding regression coefficients was also high (SE of estimate—± 10%).

PR was also found to bear a linear relationship with work load at various levels of heat stress. Further, it was evident that at all levels (a), (b) and (c), the effect of work effort on observed pulse rate was more significant than that of heat exposure during work in hot environments.

From the observed relationships between PR, CET and BSA, on the one hand, and EE, on the other, it could be suggested that it is possible to predict the physiological cost of work from easily measurable parameters on the shop floor.     

Project Indravati: Phase I. An appraisal of the natural resources of the Indravati basin,Orissa, Madhya Pradesh and Maharashtra,India

Project Indravati has been taken up to demonstrate the capabilities of remote-sensing data for the exploration of natural resources and also the structural linkages necessary to evolve a National Natural Resources Management System (NNRMS). The Geological Survey of India, the National Atlas and Thematic Mapping Organization and the Forest Survey of India are the collaborating agencies under this project. The National Bureau of Soil Survey and Land-use Planning has supplied data on soils of the area. This densely forested, undercultivated region with a relatively virgin status in mineral exploration offers ample scope for using remote-sensing techniques in evaluating its natural resource potential.

Data on geology, structure and lineaments, geomorphology, drainage, soil and vegetation were compiled and collated, based on visual interpretation of LANDSAT imagery. The area has a complex physiographic and geological history and varied soil types. Vegetation is mostly mixed deciduous types.

Two test areas, which are relatively remote and difficult to approach, have been selected for detailed aerial and multispectral scanner survey for the assessment of natural resources.     

Microstructural Characterization and Properties Evaluation of Ni-Based Hardfaced Coating on AISI 304 Stainless Steel by High Velocity Oxyfuel Coating Technique

The present study concerns a detailed investigation of microstructural evolution of nickel based hardfaced coating on AISI 304 stainless steel by high velocity oxy-fuel (HVOF) deposition technique. The work has also been extended to study the effect of coating on microhardness, wear resistance and corrosion resistance of the surface. Deposition has been conducted on sand blasted AISI 304 stainless steel by HVOF spraying technique using nickel (Ni)-based alloy [Ni: 68.4 wt pct, chromium (Cr): 17 wt pct, boron (B): 3.9 wt pct, silicon (Si): 4.9 wt pct and iron (Fe): 5.8 wt pct] of particle size 45 to 60 ??m as precursor powder. Under the optimum process parameters, deposition leads to development of nano-borides (of chromium, Cr₂B and nickel, Ni₃B) dispersion in metastable and partly amorphous gamma nickel (??-Ni) matrix. The microhardness of the coating was significantly enhanced to 935 VHN as compared to 215 VHN of as-received substrate due to dispersion of nano-borides in grain refined and partly amorphous nickel matrix. Wear resistance property under fretting wear condition against WC indenter was improved in as-deposited layer (wear rate of 4.65 × 10^?7 mm³/mm) as compared to as-received substrate (wear rate of 20.81 × 10^?7 mm³/mm). The corrosion resistance property in a 3.56 wt pct NaCl solution was also improved.