Thermally developing combined electroosmotic and pressure-driven flow of nanofluids in a microchannel under the effect of magnetic field

In the present study, the heat transfer characteristics of thermally developing magnetohydroclynamic flow of nanofluid through microchannel are delineated by following a semi analytical approach. The combined influences of pressure driven flow, electroosmotic transport and magnetic field is taken into account for the analysis of the complex microscale thermal transport processes. Solutions for the normalized temperature distributions and the Nusselt number variations, considering the simultaneous interplay of electrokinetic effects (electroosmosis), magnetic effects, Joule heating and viscous dissipation are obtained, for constant wall temperature condition. Particular attention is paid to assess the role of nanolluids in altering the transport phenomena, through variations in the effective nanoparticle volume fractions, as well as the aggregate structure of the particulate phases. It is observed that magnetohydrodynamic effect reduces advective transport of the liquid resulting in gradual reduction of heat transfer. Increase in nanoparticle volume fraction shows decrease in heat transfer. Similar effects are observed with increase in aggregate sizes of the nanoparticles. The effect of the nanofluids on system irreversibility is also studied through entropy generation analysis due to flow and heat transfer in the microchannel. Total entropy generation is found to be dominant at the thermally developing region of the microchannel, whereas it drops sharply at the thermally developed region. Presence of nanoparticles in the base fluid reduces the total entropy generation in the microchannel, thereby indicating decrease in thermodynamic irreversibility with increasing nanoparticle volume fraction. (C) 2014 Elsevier Ltd. All rights reserved.

On the strain rate sensitivity of plastic flow in metallic glasses

The nanoindentation technique was employed to examine the strain rate sensitivity, m, and its dependence on the structural state of a Zr-based bulk metallic glass (BMG). The free volume content in the BMG was varied by examining samples in the as-cast (AC), shot-peened (SP), and structurally relaxed (SR) states. Hardness values measured at different loading rates and over a temperature range of 300-423 K as well as the strain-rate jump tests conducted in the quasi-static regime at room temperature, show that m is always negative. All the load-displacement (P-h) curves in this temperature regime exhibit serrated load-displacement responses, indicating that the shear band mediated inhomogeneous plastic flow governs deformation. Such localization of flow and associated softening is the raison d'etre for the negative m. Significant levels of pile-up around the indents were also noted. The order in the average values of hardness, pile-up heights, and the displacement bursts on the P-h curves was always such that SR > AC > SP, which is also the order of increasing free volume content. These observations were utilized to discuss the reasons for the negative strain rate sensitivity, and its dependence on the structural state of metallic glasses. It is suggested that the positive values of m reported in the literature for them are possibly experimental artefacts that arise due to large pile ups around the indents which lead to erroneous estimation in hardness values. (C) 2014 Elsevier B.V. All rights reserved.

Optical Flow based on Approximate Nearest Neighbor Field

In this work, we propose an algorithm for optical flow estimation using Approximate Nearest Neighbor Fields (ANNF). Proposed optical flow estimation algorithm consists of two steps, flow initialization using ANNF maps and cost filtering. Flow initialization is done by computing the ANNF map using FeatureMatch between two consecutive frames. The ANNF map obtained represents a noisy optical flow, which is refined by making use of superpixels. The best flow associated with each superpixel is computed by optimizing a cost function. The proposed approach is evaluated on Middlebury and MPI-Sintel optical flow dataset and is found to be comparable with the state of the art methods for optical flow estimation.

Crowd Flow Segmentation based on Motion Vectors in H.264 Compressed Domain

In this work, we have explored the prospect of segmenting crowd flow in H. 264 compressed videos by merely using motion vectors. The motion vectors are extracted by partially decoding the corresponding video sequence in the H. 264 compressed domain. The region of interest ie., crowd flow region is extracted and the motion vectors that spans the region of interest is preprocessed and a collective representation of the motion vectors for the entire video is obtained. The obtained motion vectors for the corresponding video is then clustered by using EM algorithm. Finally, the clusters which converges to a single flow are merged together based on the bhattacharya distance measure between the histogram of the of the orientation of the motion vectors at the boundaries of the clusters. We had implemented our proposed approach on the complex crowd flow dataset provided by 1] and compared our results by using Jaccard measure. Since we are performing crowd flow segmentation in the compressed domain using only motion vectors, our proposed approach performs much faster compared to other pixel domain counterparts still retaining better accuracy.

A Distributed TDMA Slot Scheduling Algorithm for Spatially Correlated Contention in WSNs

In WSNs the communication traffic is often time and space correlated, where multiple nodes in a proximity start transmitting simultaneously. Such a situation is known as spatially correlated contention. The random access method to resolve such contention suffers from high collision rate, whereas the traditional distributed TDMA scheduling techniques primarily try to improve the network capacity by reducing the schedule length. Usually, the situation of spatially correlated contention persists only for a short duration, and therefore generating an optimal or suboptimal schedule is not very useful. Additionally, if an algorithm takes very long time to schedule, it will not only introduce additional delay in the data transfer but also consume more energy. In this paper, we present a distributed TDMA slot scheduling (DTSS) algorithm, which considerably reduces the time required to perform scheduling, while restricting the schedule length to the maximum degree of interference graph. The DTSS algorithm supports unicast, multicast, and broadcast scheduling, simultaneously without any modification in the protocol. We have analyzed the protocol for average case performance and also simulated it using Castalia simulator to evaluate its runtime performance. Both analytical and simulation results show that our protocol is able to considerably reduce the time required for scheduling.

On the curvature ODE associated to the Ricci flow

In the vector space of algebraic curvature operators we study the reaction ODE which is associated to the evolution equation of the Riemann curvature operator along the Ricci flow. More precisely, we give a partial classification of the zeros of this ODE up to suitable normalization and analyze the stability of a special class of zeros of the same. In particular, we show that the ODE is unstable near the curvature operators of the Riemannian product spaces where is an Einstein (locally) symmetric space of compact type and not a spherical space form when .

Compressive flow behavior of Al-Si based alloy: Role of heat treatment

The flow characteristics of a near eutectic Al-Si based cast alloy have been examined in compression at strain rates varying from 3 x 10(-4) to 10(2) s(-1) and at three different temperatures, i.e., room temperature (RT), 100 degrees C and 200 degrees C. The dependence of the flow behavior on heat treatment is studied by testing the alloy in non-heat treated (NHT) and heat treated (HT) conditions. The heat treatment has strong influence on strain rate sensitivity (SRS), strength and work hardening behavior of the alloy. It is observed that the strength of the alloy increases with increase in strain rate and it increases more rapidly above the strain rate of 10(-1) s(-1) in HT condition at all the temperatures, and at 100 degrees C and 200 degrees C in NHT condition. The thermally dependent process taking place in the HT matrix is responsible for the observed greater SRS in HT condition. The alloy in HT condition exhibits a larger work hardening rate than in NHT condition during initial stages of straining. However, the hardening rate decreases more sharply at higher strains in HT condition due to precipitate shearing and higher rate of Si particle fracture. Thermal hardening is observed at 200 degrees C in NHT condition due to precipitate formation, which results in increased SRS at higher temperatures. Thermal softening is observed in HT condition at 200 C due to precipitate coarsening, which leads to a decrease in SRS at higher temperatures. Stress simulations by a finite element method support the experimentally observed particle and matrix fracture behavior. A negative SRS and serrated flow are observed in the lower strain rate regime (3 x 10(-4)-10(-2) s(-1)) at RT and 100 degrees C, in both NHT and HT conditions. The observations show that both dynamic strain aging (DSA) and precipitate shearing play a role in serrated flow. (C) 2015 Elsevier B.V. All rights reserved.

Fully developed thermal transport in combined pressure and electroosmotically driven flow of nanofluid in a microchannel under the effect of a magnetic field

This paper critically analyzes, for the first time, the effect of nanofluid on thermally fully developed magnetohydrodynamic flows through microchannel, by considering combined effects of externally applied pressure gradient and electroosmosis. The classical boundary condition of uniform wall heat flux is considered, and the effects of viscous dissipation as well as Joule heating have been taken into account. Closed-form analytical expressions for the pertinent velocity and temperature distributions and the Nusselt number variations are obtained, in order to examine the role of nanofluids in influencing the fully developed thermal transport in electroosmotic microflows under the effect of magnetic field. Fundamental considerations are invoked to ascertain the consequences of particle agglomeration on the thermophysical properties of the nanofluid. The present theoretical formalism addresses the details of the interparticle interaction kinetics in tune with the pertinent variations in the effective particulate dimensions, volume fractions of the nanoparticles, as well as the aggregate structure of the particulate system. It is revealed that the inclusion of nanofluid changes the transport characteristics and system irreversibility to a considerable extent and can have significant consequences in the design of electroosmotically actuated microfluidic systems.

Stability of the flow in a soft tube deformed due to an applied pressure gradient

A linear stability analysis is carried out for the flow through a tube with a soft wall in order to resolve the discrepancy of a factor of 10 for the transition Reynolds number between theoretical predictions in a cylindrical tube and the experiments of Verma and Kumaran J. Fluid Mech. 705, 322 (2012)]. Here the effect of tube deformation (due to the applied pressure difference) on the mean velocity profile and pressure gradient is incorporated in the stability analysis. The tube geometry and dimensions are reconstructed from experimental images, where it is found that there is an expansion and then a contraction of the tube in the streamwise direction. The mean velocity profiles at different downstream locations and the pressure gradient, determined using computational fluid dynamics, are found to be substantially modified by the tube deformation. The velocity profiles are then used in a linear stability analysis, where the growth rates of perturbations are calculated for the flow through a tube with the wall modeled as a neo-Hookean elastic solid. The linear stability analysis is carried out for the mean velocity profiles at different downstream locations using the parallel flow approximation. The analysis indicates that the flow first becomes unstable in the downstream converging section of the tube where the flow profile is more pluglike when compared to the parabolic flow in a cylindrical tube. The flow is stable in the upstream diverging section where the deformation is maximum. The prediction for the transition Reynolds number is in good agreement with experiments, indicating that the downstream tube convergence and the consequent modification in the mean velocity profile and pressure gradient could reduce the transition Reynolds number by an order of magnitude.

Low Complexity Power and Scheduling Policies for Wireless Networks to Provide Quality of Service

We consider optimal power allocation policies for a single server, multiuser system. The power is consumed in transmission of data only. The transmission channel may experience multipath fading. We obtain very efficient, low computational complexity algorithms which minimize power and ensure stability of the data queues. We also obtain policies when the users may have mean delay constraints. If the power required is a linear function of rate then we exploit linearity and obtain linear programs with low complexity.

Performance of OFDM Systems With Best-m Feedback, Scheduling, and Delays for Uniformly Correlated Subchannels

Contemporary cellular standards, such as Long Term Evolution (LTE) and LTE-Advanced, employ orthogonal frequency-division multiplexing (OFDM) and use frequency-domain scheduling and rate adaptation. In conjunction with feedback reduction schemes, high downlink spectral efficiencies are achieved while limiting the uplink feedback overhead. One such important scheme that has been adopted by these standards is best-m feedback, in which every user feeds back its m largest subchannel (SC) power gains and their corresponding indices. We analyze the single cell average throughput of an OFDM system with uniformly correlated SC gains that employs best-m feedback and discrete rate adaptation. Our model incorporates three schedulers that cover a wide range of the throughput versus fairness tradeoff and feedback delay. We show that, for small m, correlation significantly reduces average throughput with best-m feedback. This result is pertinent as even in typical dispersive channels, correlation is high. We observe that the schedulers exhibit varied sensitivities to correlation and feedback delay. The analysis also leads to insightful expressions for the average throughput in the asymptotic regime of a large number of users.

THREE-LAYER FLUID FLOW OVER A SMALL OBSTRUCTION ON THE BOTTOM OF A CHANNEL

Many boundary value problems occur in a natural way while studying fluid flow problems in a channel. The solutions of two such boundary value problems are obtained and analysed in the context of flow problems involving three layers of fluids of different constant densities in a channel, associated with an impermeable bottom that has a small undulation. The top surface of the channel is either bounded by a rigid lid or free to the atmosphere. The fluid in each layer is assumed to be inviscid and incompressible, and the flow is irrotational and two-dimensional. Only waves that are stationary with respect to the bottom profile are considered in this paper. The effect of surface tension is neglected. In the process of obtaining solutions for both the problems, regular perturbation analysis along with a Fourier transform technique is employed to derive the first-order corrections of some important physical quantities. Two types of bottom topography, such as concave and convex, are considered to derive the profiles of the interfaces. We observe that the profiles are oscillatory in nature, representing waves of variable amplitude with distinct wave numbers propagating downstream and with no wave upstream. The observations are presented in tabular and graphical forms.

An Implementation of Partitioned Scheduling Scheme for Hard Real-Time Tasks in Multicore Linux with Fair Share for Linux Tasks

The correctness of a hard real-time system depends its ability to meet all its deadlines. Existing real-time systems use either a pure real-time scheduler or a real-time scheduler embedded as a real-time scheduling class in the scheduler of an operating system (OS). Existing implementations of schedulers in multicore systems that support real-time and non-real-time tasks, permit the execution of non-real-time tasks in all the cores with priorities lower than those of real-time tasks, but interrupts and softirqs associated with these non-real-time tasks can execute in any core with priorities higher than those of real-time tasks. As a result, the execution overhead of real-time tasks is quite large in these systems, which, in turn, affects their runtime. In order that the hard real-time tasks can be executed in such systems with minimal interference from other Linux tasks, we propose, in this paper, an integrated scheduler architecture, called SchedISA, which aims to considerably reduce the execution overhead of real-time tasks in these systems. In order to test the efficacy of the proposed scheduler, we implemented partitioned earliest deadline first (P-EDF) scheduling algorithm in SchedISA on Linux kernel, version 3.8, and conducted experiments on Intel core i7 processor with eight logical cores. We compared the execution overhead of real-time tasks in the above implementation of SchedISA with that in SCHED_DEADLINE's P-EDF implementation, which concurrently executes real-time and non-real-time tasks in Linux OS in all the cores. The experimental results show that the execution overhead of real-time tasks in the above implementation of SchedISA is considerably less than that in SCHED_DEADLINE. We believe that, with further refinement of SchedISA, the execution overhead of real-time tasks in SchedISA can be reduced to a predictable maximum, making it suitable for scheduling hard real-time tasks without affecting the CPU share of Linux tasks.

Automated cell viability assessment using a microfluidics based portable imaging flow analyzer

In this work, we report a system-level integration of portable microscopy and microfluidics for the realization of optofluidic imaging flow analyzer with a throughput of 450 cells/s. With the use of a cellphone augmented with off-the-shelf optical components and custom designed microfluidics, we demonstrate a portable optofluidic imaging flow analyzer. A multiple microfluidic channel geometry was employed to demonstrate the enhancement of throughput in the context of low frame-rate imaging systems. Using the cell-phone based digital imaging flow analyzer, we have imaged yeast cells present in a suspension. By digitally processing the recorded videos of the flow stream on the cellphone, we demonstrated an automated cell viability assessment of the yeast cell population. In addition, we also demonstrate the suitability of the system for blood cell counting. (C) 2015 AIP Publishing LLC.

Evaluating Methods to Predict Streamflow at Ungauged Sites using Regional Flow Duration Curves: A Case Study

Precise information on streamflows is of major importance for planning and monitoring of water resources schemes related to hydro power, water supply, irrigation, flood control, and for maintaining ecosystem. Engineers encounter challenges when streamflow data are either unavailable or inadequate at target locations. To address these challenges, there have been efforts to develop methodologies that facilitate prediction of streamflow at ungauged sites. Conventionally, time intensive and data exhaustive rainfall-runoff models are used to arrive at streamflow at ungauged sites. Most recent studies show improved methods based on regionalization using Flow Duration Curves (FDCs). A FDC is a graphical representation of streamflow variability, which is a plot between streamflow values and their corresponding exceedance probabilities that are determined using a plotting position formula. It provides information on the percentage of time any specified magnitude of streamflow is equaled or exceeded. The present study assesses the effectiveness of two methods to predict streamflow at ungauged sites by application to catchments in Mahanadi river basin, India. The methods considered are (i) Regional flow duration curve method, and (ii) Area Ratio method. The first method involves (a) the development of regression relationships between percentile flows and attributes of catchments in the study area, (b) use of the relationships to construct regional FDC for the ungauged site, and (c) use of a spatial interpolation technique to decode information in FDC to construct streamflow time series for the ungauged site. Area ratio method is conventionally used to transfer streamflow related information from gauged sites to ungauged sites. Attributes that have been considered for the analysis include variables representing hydrology, climatology, topography, land-use/land- cover and soil properties corresponding to catchments in the study area. Effectiveness of the presented methods is assessed using jack knife cross-validation. Conclusions based on the study are presented and discussed. (C) 2015 The Authors. Published by Elsevier B.V.