Analysis of Entropy Generation During Mixed Convective Heat Transfer of Nanofluids Past a Rotating Circular Cylinder

The entropy generation due to mixed convective heat transfer of nanofluids past a rotating circular cylinder placed in a uniform cross stream is investigated via streamline upwind Petrov-Galerkin based finite element method. Nanosized copper (Cu) particles suspended in water are used with Prandtl number (Pr)=6.9. The computations are carried out at a representative Reynolds number (Re) of 100. The dimensionless cylinder rotation rate, a, is varied between 0 and 2. The range of nanoparticle volume fractions (phi) considered is 0 <= phi <= 5%. Effect of aiding buoyancy is brought about by considering two fixed values of the Richardson number (Ri) as 0.5 and 1.0. A new model for predicting the effective viscosity and thermal conductivity of dilute suspensions of nanoscale colloidal particles is presented. The model addresses the details of the agglomeration-deagglomeration in tune with the pertinent variations in the effective particulate dimensions, volume fractions, as well as the aggregate structure of the particulate system. The total entropy generation is found to decrease sharply with cylinder rotation rates and nanoparticle volume fractions. Increase in nanoparticle agglomeration shows decrease in heat transfer irreversibility. The Bejan number falls sharply with increase in alpha and phi.

Super Resolution Using a Single Image Dictionary

To perform super resolution of low resolution images, state-of-the-art methods are based on learning a pair of lowresolution and high-resolution dictionaries from multiple images. These trained dictionaries are used to replace patches in lowresolution image with appropriate matching patches from the high-resolution dictionary. In this paper we propose using a single common image as dictionary, in conjunction with approximate nearest neighbour fields (ANNF) to perform super resolution (SR). By using a common source image, we are able to bypass the learning phase and also able to reduce the dictionary from a collection of hundreds of images to a single image. By adapting recent developments in ANNF computation, to suit super-resolution, we are able to perform much faster and accurate SR than existing techniques. To establish this claim, we compare the proposed algorithm against various state-of-the-art algorithms, and show that we are able to achieve b etter and faster reconstruction without any training.

Sparse coding based VLAD for efficient image retrieval

Representing images and videos in the form of compact codes has emerged as an important research interest in the vision community, in the context of web scale image/video search. Recently proposed Vector of Locally Aggregated Descriptors (VLAD), has been shown to outperform the existing retrieval techniques, while giving a desired compact representation. VLAD aggregates the local features of an image in the feature space. In this paper, we propose to represent the local features extracted from an image, as sparse codes over an over-complete dictionary, which is obtained by K-SVD based dictionary training algorithm. The proposed VLAD aggregates the residuals in the space of these sparse codes, to obtain a compact representation for the image. Experiments are performed over the `Holidays' database using SIFT features. The performance of the proposed method is compared with the original VLAD. The 4% increment in the mean average precision (mAP) indicates the better retrieval performance of the proposed sparse coding based VLAD.

Efficient generation of diffraction-limited multi-sheet pattern for biological imaging

We demonstrate a new technique to generate multiple light-sheets for fluorescence microscopy. This is possible by illuminating the cylindrical lens using multiple copies of Gaussian beams. A diffraction grating placed just before the cylindrical lens splits the incident Gaussian beam into multiple beams traveling at different angles. Subsequently, this gives rise to diffraction-limited light-sheets after the Gaussian beams pass through the combined cylindrical lens-objective sub-system. Direct measurement of field at and around the focus of objective lens shows multi-sheet pattern with an average thickness of 7.5 mu m and inter-sheet separation of 380 mu m. Employing an independent orthogonal detection sub-system, we successfully imaged fluorescently-coated yeast cells (approximate to 4 mu m) encaged in agarose gel-matrix. Such a diffraction-limited sheet-pattern equipped with dedicated detection system may find immediate applications in the field of optical microscopy and fluorescence imaging. (C) 2015 Optical Society of America

SWEETENING OF BIOGAS IN SPRAY TOWERS FOR POWER GENERATION

This paper presents the experience of the new design of using impinging jet spray columns for scrubbing hydrogen sulfide from biogas that has been developed by Indian Institute of Science and patented. The process uses a chelated polyvalent metal ion which oxidizes the hydrogen sulfide to sulfur as a precipitate. The sulfur generated is filtered and the scrubbing liquid recycled after oxidation. The process involves in bringing contact the sour gas with chelated liquid in the spray columns where H2S reacts with chelated Fe3+ and precipitates as sulfur, whereas Fe3+ gets reduced to Fe2+. Fe2+ is regenerated to Fe3+ by reaction of oxygen in air in a separate packed column. The regenerated liquid is recirculated. Sulfur is filtered and separated as a byproduct. The paper presents the experience in using the spray towers for hydrogen sulfide removal and further use of the clean gas for generating power using gas engines. The maximum allowable limit of H2S for the gas engine is 200 ppm (v/v) in order to prevent any corrosion of engine parts and fouling of the lubricating oil. With the current ISET process, the hydrogen sulfide from the biogas is cleaned to less than 100 ppm (v/v) and the sweet gas is used for power generation. The system is designed for 550 NM3/hr of biogas and inlet H2S concentration of 2.5 %. The inlet concentration of the H2S is about 1 - 1.5 % and average measured outlet concentration is about 30 ppm, with an average gas flow of about 300 - 350 NM3/hr, which is the current gas production rate. The sweet gas is used for power generation in a 1.2 MWe V 12 engine. The average power generation is about 650 - 750 kWe, which is the captive load of the industry. The plant is a CHP (combined heat power) unit with heat from the cylinder cooling and flue being recovered for hot water and steam generation respectively. The specific fuel consumption is 2.29 kWh/m(3) of gas. The system has been in operation for more than 13,000 hours in last one year in the industry. About 8.4 million units of electricity has been generated scrubbing about 2.1 million m3 of gas. Performance of the scrubber and the engine is discussed at daily performance level and also the overall performance with an environment sustenance by precipitating over 27 tons of sulfur.

B-Spline potential function for maximum a-posteriori image reconstruction in fluorescence microscopy

An iterative image reconstruction technique employing B-Spline potential function in a Bayesian framework is proposed for fluorescence microscopy images. B-splines are piecewise polynomials with smooth transition, compact support and are the shortest polynomial splines. Incorporation of the B-spline potential function in the maximum-a-posteriori reconstruction technique resulted in improved contrast, enhanced resolution and substantial background reduction. The proposed technique is validated on simulated data as well as on the images acquired from fluorescence microscopes (widefield, confocal laser scanning fluorescence and super-resolution 4Pi microscopy). A comparative study of the proposed technique with the state-of-art maximum likelihood (ML) and maximum-a-posteriori (MAP) with quadratic potential function shows its superiority over the others. B-Spline MAP technique can find applications in several imaging modalities of fluorescence microscopy like selective plane illumination microscopy, localization microscopy and STED. (C) 2015 Author(s).

Extremely High Near Field Enhancement in a Novel Plasmonic Nano Material used for Photovoltage Generation

Enhancement of localized electric field near metal (plasmonic) nanostructures can have various interesting applications in sensing, imaging, photovoltage generation etc., for which significant efforts are aimed towards developing plasmonic systems with well designed and large electromagnetic response. In this paper, we discuss the wafer scale fabrication and optical characterization of a unique three dimensional plasmonic material. The near field enhancement in the visible range of the electromagnetic spectrum obtained in these structures (order of 106), is close to the fundamental limit that can be obtained in this and similar EM field enhancement schemes. The large near field enhancement has been reflected in a huge Raman signal of graphene layer in close proximity to the plasmonic system, which has been validated with FEM simulations. We have integrated graphene photodetectors with this material to obtain record photovoltage generation, with responsivity as high as A/W. As far as we know, this is the highest sensitivity obtained in any plasmonic-graphene hybrid photodetection system till date.

Synthetic image super resolution using FeatureMatch

In this paper, we propose a super resolution (SR) method for synthetic images using FeatureMatch. Existing state-of-the-art super resolution methods are learning based methods, where a pair of low-resolution and high-resolution dictionary pair are trained, and this trained pair is used to replace patches in low-resolution image with appropriate matching patches from the high-resolution dictionary. In this paper, we show that by using Approximate Nearest Neighbour Fields (ANNF), and a common source image, we can by-pass the learning phase, and use a single image for dictionary. Thus, reducing the dictionary from a collection obtained from hundreds of training images, to a single image. We show that by modifying the latest developments in ANNF computation, to suit super resolution, we can perform much faster and more accurate SR than existing techniques. To establish this claim we will compare our algorithm against various state-of-the-art algorithms, and show that we are able to achieve better and faster reconstruction without any training phase.

Generation of Temperature Dependent Transversely Isotropic Properties for Zigzag and Armchair Single-Walled Carbon Nanotubes

Finite element analysis has been carried out to obtain temperature dependent transversely isotropic properties of the single-walled carbon nanotubes (SWCNTs). Finite element models of SWCNTs are generated by specifying the C-C bond rigidities. The five independent transversely isotropic properties for different chiralities are evaluated using the stress fields of thick-walled cylinders and the elastic deformations of SWCNTs subjected to pure extension, internal pressure and pure torsion loads. Empirical relations are provided for the five independent elastic constants useful to armchair and zigzag SWCNTs.

Real-time maximum a-posteriori image reconstruction for fluorescence microscopy

Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU) based real-time maximum a-posteriori (MAP) image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads) results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA) efficiently execute the iterative image reconstruction algorithm that is similar to 200-fold faster (for large dataset) when compared to existing CPU based systems. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

A Split-and-Merge Dictionary Learning Algorithm for Sparse Representation: Application to Image Denoising

In big data image/video analytics, we encounter the problem of learning an over-complete dictionary for sparse representation from a large training dataset, which cannot be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm that exploits the inherent clustered structure of the training data and make use of a divide-and-conquer approach. The fundamental idea behind the algorithm is to partition the training dataset into smaller clusters, and learn local dictionaries for each cluster. Subsequently, the local dictionaries are merged to form a global dictionary. Merging is done by solving another dictionary learning problem on the atoms of the locally trained dictionaries. This algorithm is referred to as the split-and-merge algorithm. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy, which operates on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.

GROUND COOLING SYSTEM FOR IMPROVING THE EFFICIENCY OF LOW TEMPERATURE POWER GENERATION

This paper presents an analysis of an organic Rankine cycle (ORC) with dry cooling system aided by an earth-coupled passive cooling system. Several organic fluids were considered as working fluids in the ORC in the temperature range of 125-200 degrees C. An earth-air-heat-exchanger (EMU) is studied for a location in the United States (Las Vegas) and another in India (New Delhi), to pre cool the ambient air before entering an air-cooled condenser (ACC). It was observed that the efficiency of the system improved by 1-3% for the system located in Las Vegas and fluctuations associated with temperature variations of the ambient air were also reduced when the EAHE system was used. A ground-coupled heat pump (GCHP) is also studied for these locations where cooling water is pre cooled in an underground buried pipe before entering a condenser heat exchanger in a closed loop. The area of the buried pipe and the condenser size are calculated per kW of power generation for various working fluids.

ADVANCED LOW PRESSURE CYCLE FOR CONCENTRATED SOLAR POWER GENERATION

Turbine inlet pressures of similar to 300 bar in case of CO2 based cycles call for redesigning the cycle in such a way that the optimum high side pressures are restricted to the discharge pressure limits imposed by currently available commercial compressors (similar to 150 bar) for distributed power generation. This leads to a cycle which is a combination of a transcritical condensing and a subcritical cycle with an intercooler and a bifurcation system in it. Using a realistic thermodynamic model, it is predicted that the cycle with the working fluid as a non-flammable mixture of 48.5 % propane and rest CO2 delivers similar to 37.2 % efficiency at 873 K with a high and a low side pressure of 150 and 26 bar respectively. This is in contrast to the best efficiency of similar to 36.1 % offered by a transcritical condensing cycle with the same working fluid at a high side pressure of similar to 300 bar

Digital image analysis around isotropic points for photoelastic pattern recognition

Fringe tracking and fringe order assignment have become the central topics of current research in digital photoelasticity. Isotropic points (IPs) appearing in low fringe order zones are often either overlooked or entirely missed in conventional as well as digital photoelasticity. We aim to highlight image processing for characterizing IPs in an isochromatic fringe field. By resorting to a global analytical solution of a circular disk, sensitivity of IPs to small changes in far-field loading on the disk is highlighted. A local theory supplements the global closed-form solutions of three-, four-, and six-point loading configurations of circular disk. The local theoretical concepts developed in this paper are demonstrated through digital image analysis of isochromatics in circular disks subjected to three-and four-point loads. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)