Showing papers by "P A College of Engineering published in 2017"

Computational Fluid Dynamics in Turbomachinery: A Review of State of the Art

Abstract: Computational fluid dynamics (CFD) plays an essential role to analyze fluid flows and heat transfer situations by using numerical methods. Turbomachines involve internal and external fluid flow problems in compressors and turbines. CFD at present is one of the most important tools to design and analyze all types of turbomachinery. The main purpose of this paper is to review the state of the art work carried out in the field of turbomachinery using CFD. Literature review of research work pertaining to CFD analysis in turbines, compressors and centrifugal pumps are described. Various issues of CFD codes used in turbomachinery and its parallelization strategy adopted are highlighted. Furthermore, the prevailing merits and demerits of CFD in turbomachinery are provided. Open areas pertinent to CFD investigation in turbomachinery and CFD code parallelization are also described.

Parallelization Strategies for Computational Fluid Dynamics Software: State of the Art Review

Abstract: Computational fluid dynamics (CFD) is one of the most emerging fields of fluid mechanics used to analyze fluid flow situation. This analysis is based on simulations carried out on computing machines. For complex configurations, the grid points are so large that the computational time required to obtain the results are very high. Parallel computing is adopted to reduce the computational time of CFD by utilizing the available resource of computing. Parallel computing tools like OpenMP, MPI, CUDA, combination of these and few others are used to achieve parallelization of CFD software. This article provides a comprehensive state of the art review of important CFD areas and parallelization strategies for the related software. Issues related to the computational time complexities and parallelization of CFD software are highlighted. Benefits and issues of using various parallel computing tools for parallelization of CFD software are briefed. Open areas of CFD where parallelization is not much attempted are identified and parallel computing tools which can be useful for parallelization of CFD software are spotlighted. Few suggestions for future work in parallel computing of CFD software are also provided.

Fault detection and recovery scheme for routing and lifetime enhancement in WSN

Abstract: In WSNs, failures are unavoidable due to the inhospitable environment and unattended deployment. The node failure leads to disconnection from the network and causes network partitioning. We propose to develop a fault detection and recovery scheme where the sink generates an agent packet and the Agent forms a query path towards the dead or faulty node. Here, sink periodically broadcasts the Agent packet to all its neighbor nodes. The receiving node randomly makes a decision as whether to forward the packet or not thereby detecting the dead or faulty nodes. After detecting a node failure or dead node, the connectivity is restored using Least-Disruptive Topology Repair (LeDiR) without extending the length of the shortest path among nodes compared to the pre failure topology. LeDiR replaces the faulty node with block movement.

Influence of Silicon Carbide Nanopowder in R134a Refrigerant Used in Vapor Compression Refrigeration System

Abstract: This paper deals with the influence of silicon carbide (SiC) nanopowder in R134 a refrigerant used in a vapor compression refrigeration system. The performance study was done by mixing a SiC nanopowder in R134a refrigerant. The energy consumption of the R134a refrigerant with SiC nanoparticles mixture saves 20% energy with 0.25% mass fraction of SiC nanoparticles when compared to the R134a system. The COP of the refrigerant R134a system is 1.24 whereas COP for R134a-SiC nanopowder is 1.81. The SiC nanopowder is cryogenically treated at −196∘C for 24 h and the COP is found out. The results show that the COP of R134a-SiC nanopowder and R134a-cryo SiC (cryogenically treated silicon carbide nanopowder) is increased when compared to the R134a conventional refrigeration system.

A fuzzy neural network based framework to discover user access patterns from web log data

Abstract: Clustering data from web user sessions is extensively applied to extract customer usage behavior to serve customized content to individual users. Due to the human involvement, web usage data usually contain noisy, incomplete and vague information. Neural networks have the capability to extract embedded knowledge in the form of user session clusters from the huge web usage data. Moreover, they provide tolerance against imperfect and noisy data. Fuzzy sets are another popular tool utilized for handling uncertainty and vagueness hidden in the data. In this paper a fuzzy neural clustering network (FNCN) based framework is proposed that makes use of the fuzzy membership concept of fuzzy c-means (FCM) clustering and the learning rate of a modified self-organizing map (MSOM) neural network model and tries to minimize the weighted sum of the squared error. FNCN is applied to cluster the users’ web access data extracted from the web logs of an educational institution’s proxy web server. The performance of FNCN is compared with FCM and MSOM based clustering methods using various validity indexes. Our results show that FNCN produces better quality of clusters than FCM and MSOM.

An evaluation of MapReduce framework in cluster analysis

Abstract: Data is growing exponentially due to the World Wide Web and scientific enhancements, requires proper strategies and techniques to deal with it. Thus, it requires increasing the computational requirements. Efficient processing paradigms and smart implementation architecture is the key to meet the scalability and performance requirements in large scale data analysis. Clustering is one of the popular data mining techniques to analyse datasets. MapReduce programming paradigm, on the top of Hadoop distributed architecture, is widely used in today's world in order to obtain efficiency for large dataset clustering. In this work, we have experimented and validated the efficiency of K-means clustering algorithm in MapReduce paradigm over hadoop architecture while processing different sized datasets in combination of different hadoop cluster sizes.

Heat and Mass Transfer of a Casson Nanofluid Flow Over a Porous Surface With Dissipation, Radiation, and Chemical Reaction

Abstract: Casson nanofluid flow with dissipation, radiation, and chemical reaction in the presence of a temperature gradient dependent heat sink subject to suction is analyzed. Hence, this paper mainly deals nanofluids with nanoparticles Cu, Au, Ag, Al, Al2O3, and TiO2 and with base fluid water. Prescribed surface temperature and concentration boundary conditions are employed on the porous surface. Suitable similarity transformations are introduced for converting nonlinear partial differential equations into the nonlinear ordinary differential equations and then solved by analytically. The influence of various physical parameters such as the nanoparticle volume fraction, Casson fluid parameter, suction parameter, permeability parameter, heat sink parameter, Prandtl number, Eckert number, radiation parameter, Schmidt number, and chemical reaction parameter over the velocity, temperature, and species concentration of nanofluid Cu-water is examined by using graphs. Skin friction coefficient, Nusselt number, and Sherwood number of various nanofluids with nanoparticles (Cu, Ag, Au, Al, Al2O3, and TiO2) are tabulated and analyzed.

Experimental Exploration of Support Vector Machine for Cancer Cell Classification

Abstract: text classification is the task of automatically categorizing collections of electronic textual documents into their predefined classes, based on their contents. Due to the increase in the amount of text data in these recent years, document classification has emerged in the form of text classification systems. They have been widely implemented in a large number of applications such as spam filtering, emails, knowledge repositories and ontology mapping. The main essence is to propose a text classification technique based on the feature selection and reduction of the feature vector dimensionality and increase the classification accuracy using pre-processing. This paper gives the detailed study on how support vector machine (SVM) can be used to classify uncertain data. SVM is a powerful and supervised learning sample based on the lowest structural risk principle. During training, this algorithm creates a hyperplane for separating positive and negative samples. The type of kernel used for SVM classifier will be having a major impact on classification results. In this paper Breast Cancer Wisconsin (Diagnostic) Data Sets are used in order to classify using four types of SVM kernel methods such as linear, polynomial, sigmoid and radial. Classification results obtained reveal that radial kernel method is best-suited data sets. In order to measure the suitability of kernel method, various factors are compared from classification results such as accuracy, kappa value, sensitivity, specificity precision etc.

An evaluation of Hadoop cluster efficiency in document clustering using parallel K-means

Abstract: One of the significant data mining techniques is clustering. Due to digitalization and globalization of each work space, large datasets are being generated rapidly. Such large dataset clustering is a challenge for traditional sequential clustering algorithms as it requires large execution time to cluster such datasets. Distributed parallel architectures and algorithms are thus helpful to achieve performance and scalability requirement of clustering large datasets. In this study, we design and experiment a parallel k-means algorithm using MapReduce programming model and compared the result with sequential k-means for clustering varying size of document dataset. The result demonstrates that proposed k-means obtains higher performance and outperformed sequential k-means while clustering documents.

Continuous set of image processing methodology for efficient image retrieval using BOW SHIFT and SURF features for emerging image processing applications

Abstract: The goal of this research is to construct and develop an innovative retrieval of the image under various aspects. One of the most attracted and drastically growing researches is relevant image retrieval for various emerging applications. Still Image retrieval is an effective research due to the necessity of image processing and image retrieval is applied in various emerging applications like satellite image processing, medical image processing and underwater acoustic image processing. Consequently, many approaches have been proposed by various earlier research works but the complete output is not yet been satisfied. In accordance to the literature survey it is come to know that BOW Bag-of-Visual-Words is one of the methods used in Image Retrieval. In this paper, a Scale Invariant Feature Transformation method (SIFT) and Speeded-Up Robust Features (SURF) method is used with Bag of Words (BOW) model called as SIFT, SURF, Bag of Visual Words SSBOVW. Both SIFT and SURF methods are used as local descriptor to deliver the signatures of the images which are invariant in scaling and rotation transformations. To increase the efficiency of the proposed approach the retrieved features are classified using MSVM (Multi Class Support Vector) to fetch the accurate image from the large database. The above discussed sequence of procedure is implemented and experimented in MATLAB software and the final out comes are verified.

An Experimental Study on the Thermal Properties and Electrical Properties of Polylactide Doped with Nano Aluminium Oxide and Nano Cupric Oxide

Abstract: The research on polylactide has been trending over the past 10 years as it is a versatile biopolymer which finds applications in food packaging and medical industries. In this research, nano aluminium oxide and nano cupric oxide have been impregnated into polylactide matrix using sonication and the nano composite thin films were prepared using solution casting technique. The thermal characterization of the neat and doped polymer films were conducted using thermogravimetric analysis and differential scanning calorimetry. the addition of nano aluminium oxide and nano cupric oxide increased the glass transition temperature and melting temperature of the samples in comparison with neat polylactide. Degree of crystallinity of all the doped samples increased with respect to the neat sample except for the sample doped with 1 mg nano aluminium oxide. The I–V characterization of the neat and doped samples revealed that addition of the nano powders reduced the resistivity of PLA by 35–45%. These results recommend the use of polylactide doped with nano aluminium oxide and nano cupric oxide as a potential semiconducting polymeric materials.

An experimental investigation on performance and emission parameters of a multi-cylinder SI engine with gasoline–LPG dual fuel mode of operation

Abstract: The present study deals with the performance and emission characteristics of a multi-point fuel injection (MPFI) spark ignition (SI) engine in gasoline�liquefied petroleum gas (LPG) dual fuel mode of operation. The LPG�gasoline ratio varied from 0 to 100% by controlling the injector signals at various speed and load conditions. Experiments show that the power output decreases with increase in speed and LPG content at lower load marginally due to lower volumetric efficiency. At higher load and lower speed conditions as the percentage of LPG increases there is not much difference in the power output. Results also reveal that 50% LPGflow gives maximum efficiency at full load condition and 4000 rpm due to lower fuel consumption. With 50% usage of LPG, the average increase in brake thermal efficiency (BTE) is 2% till the engine speed of 4000 rpm at full load (100%) and half load (50%) conditions. As the LPG ratio increases the engine will work in the lean region for all speed and load conditions. For all load and speed conditions, results reveal that 100% LPG will give minimum hydrocarbon (HC) and carbon monoxide (CO) emissions. Oxide of nitrogen (NOX) emissions are higher for 100% LPG. However 50% LPG flow gives good agreement of NOX, HC and CO emissions when compared with gasoline operation

Influence of Prandtl number on heat transfer of a flat vertical plate

Abstract: Liquid metals, such as sodium (Na), lead (Pb), and lead-bismuth (Pb-Bi) eutectic (e), are considered as potential coolants for the fast spectrum nuclear reactors of the next generation. So the main objective of this paper is to study the heat transfer and fluid flow characteristics of liquid metal coolants flowing over a nuclear fuel element having uniform volumetric energy generation. Stream function vorticity formulation method was used to solve the full Navier Stokes equations governing the flow. The energy equation was solved using central finite difference method. For the two-dimensional steady state heat conduction and stream-function equation, the discretisation was done in the form suitable to solve using 'line-by-line Gauss-Seidel' solution technique whereas the discretisation of vorticity transport and energy equations was done using Alternating Direction Implicit (ADI) scheme. After discretisation the systems of algebraic equations were solved using 'Thomas algorithm'. The complete work was done by writing a well-validated indigenous computer code using C-language. The parameters considered for the study were: aspect ratio of fuel element, Ar, conduction-convection parameter Ncc, total energy generation parameter Qt, and flow Reynolds number ReH. The results obtained can be used to minimise the maximum temperature in the fuel element (hot spots) and prevent its melting.

Design of energy aware collection tree protocol in Wireless Sensor Network

Abstract: In today's world, WSN (Wireless Sensor network) have gained a lot of attention due to its applications. Wireless Sensor Networks (WSNs) consist of small nodes with sensing, computation, and wireless communications capabilities. Designing a routing protocol in WSN is a very challenging task many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. The focus, however, has been given to the routing protocols which might differ depending on the application and network architecture. In this paper we have discussed a routing protocol CTP (Collection Tree Protocol) which is responsible for constructing and maintaining the routing tree to send data to the root node. We have proposed an algorithm which saves energy in CTP in routing by recovering a damaged route. We have run the CTP protocol on TOSSIM Simulator in Tinyos2.1.2.

Mobile app: Instant record of construction site detail through electronic signature

Abstract: Android is one of the present day innovation which is developing quick and play in everybody's grasp. A portable application is produced to keep up the building site points of interest through electronic mark. It encourages the client to record the report of every day compensation and the participation report through electronic mark. Electronic marks, as transcribed marks, are one of a kind to every underwriter and it is planned to tackle the issue of altering. The application spares the electronic mark as picture design. In the present focused business atmosphere, printing archives just to catch a client mark is not just totally obsolete in tablet-unavoidable regular day to day existence but at the same time is an incredible exercise in futility and cash. It stores and gives the record of detailed information on labor attendance, labor salary, material stock and also calculates the accurate building expenses. All the details are recorded through electronic signature and it gives information about by whom and when it was signed. While getting the signature, Integrity is maintained throughout the entire process. An electronic signature is proposed to give a protected and exact distinguishing proof technique for the signatory to give a consistent exchange. Meanings of electronic marks shift contingent upon the appropriate locale. Marking computerized records with a manually written mark that is forensically identifiable is unmistakably the favored decision in a building development.

Adaptive Control Technique for Generator Side Power System Voltage Stability at Wind Power Station

Abstract: Voltage instability and over voltage are one of the main problems in today wind industry. In wind power production system the output is depends upon the nature of source called wind. But that source is not constant one. It may be varying depending upon the climate. Due to that oscillation the output voltage from the generator side is instability. These problems are becoming a more serious concern with the ever-increasing utilization and higher loading of existing transmission systems, particularly with increasing energy wastage, energy demands, and competitive generation and supply requirements. Our aim is to improve power system voltage stability by enhancing generator reactive, active power control and voltage control. Adaptive feedback system along with the HSVC ways to improve power system voltage stability by enhancing generator controls in the wind power station. To solve this problem adaptive exciter system are used which will adjust the load voltage and the system voltage with that of the reference voltage. The generator output voltage is applied to the adaptive exciter controller (AEC) which updates its stability weight value on demand. The design of modules can be done in Xilinx system generator (XSG). The modules that are designed in system generator can be implemented in FPGA.

Rtpg based built in self test for test compression

Abstract: Built In Self Test (BIST) is used to test the working functions of IC circuit and it is one of the merit in IC’s to check all the working functions inside the IC circuit. And one of the other cons of BIST is it does not need any other additional device or circuit to test the functions of IC as it has additional power and additional circuit than other devices. Thus BIST reduces the power consumption of addition circuit by consuming considerable power. There is no solution to overcome the problem of consumption of larger power even there are vast methods to reduce consumption of power. But one of the best existing power reduction method in BIST is PRPG, as it gives pseudo Random patterns to test. But it also produce considerable power consumption due to toggling and repetition of patterns. Therefore we can use RTPG to overcome the drawbacks of toggling and repetition in PRPG. RTPG is the Random Test Pattern Generator uses Multiple in Input Signature Register (MIST) in order to reduce the repetition. So the power consumption can be reduced by reducing the pattern in our proposed system.