Showing posts with label impact factor. Show all posts
Showing posts with label impact factor. Show all posts

Wednesday, 16 September 2015

Manufacturing Techniques of Fibreglass Reinforced Composites

IJSRD found Good research work on Mechanical research area.

Abstract— Combining a high strength fibre with a polymeric matrix produces a composite material with higher stiffness and strength. There are many techniques to produce composite materials, among which few techniques are discussed here based on its process, capabilities and application of composite parts. Among which hand lay-up, vacuum infusion, resin transfer molding and sheet molding compound are widely used. The prepreg is widely used for manufacturing composite parts.

Key words: Fibreglass Cloth, Fibre Reinforced Composites, Prepreg, Vacuum Infusion, Sheet Molding Compound

Introduction

The global nature of today’s reinforced plastics industry creates a demand from all over the world. To produce a composite item, two basic components are required, these being a synthetic resin and a strong fibre [1]. The resin, which can be in the form of a polyester, epoxy or vinyl ester, is normally supplied as a viscous liquid, which sets to a hard solid when suitably activated [1]. The fibre may be glass, carbon, or a combination of some or all of these. What makes composites unique is the fact that the material of construction and the end product are produced simultaneously. Using a suitable mould, layers of fibre are impregnated with activated resin until the required thickness is achieved [1]. After completion, the mould is removed, which further can be used to produce more no. of identical items. These products are FRP cylinders, FRP sheets, FRP components for Transformers, and switchgears products. In the manufacturing of the Fibreglass epoxy sheets are more difficult tasks as it has many intermediate processes to manufactured sheets. The sheets are the combination of the fibreglass cloth and resin matrix that bond with the fibreglass cloth to make highly strength composites. Glass fibres fall into two categories: low-cost general-purpose fibres and premium special-purpose fibres. Over 90 % of all glass fibres are general- purpose products. These fibres are known by the designation E-glass. The remaining glass fibres are premium special-purpose products [2]. Specialpurpose fibres, which are of commercial significance in the market today, include glass fibres with high corrosion resistance (ECR-glass), high strength (S-, R-, and T Eglass), with low dielectric constants (D-glass), high-strength fibres, and pure silica or quartz fibres, which can be used at ultrahigh temperatures[2].

Fig. Schematic Illustration of the Vacuum Enhanced Resin Infusion Technology (Verity)

Vacuum Infusion:

The most popular term to describe vacuum infusion processes are Vacuum Assisted Resin Transfer Moulding (VARTM), Vacuum Assisted Resin Infusion Moulding (VARIM) etc, basically the same technology, and describe methods based on the impregnation of dry reinforcement by liquid thermoset resin driven under vacuum, and this technique made to reduce the void content inside the molded composites. With vacuum bag moulding, the bags are used to evacuate the air from laminate and to generate the atmospheric pressure required for compaction over the mold [7]. Infusion processes are plagued by limitations such as lower fibre volume fraction, lack of uniform resin distribution, higher porosity, control on thickness of part, clogging of resin and vacuum feed lines. CSIR-NAL has developed a proprietary infusion process called VERITy (Vacuum Enhanced Resin Infusion Technology), Kundan et al. (2013), to overcome the above limitations. The process is designed in such a way that it is scalable from a laminate level to a complex cocured primary structure like the wing of a transport aircraft. A schematic of the VERITy process is shown in Fig

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Friday, 21 August 2015

Emergent Artificial Intelligence

What happens when a computer can learn on the job?
Artificial intelligence (AI) is, in simple terms, the science of doing by computer the things that people can do. Over recent years, AI has advanced significantly: most of us now use smartphones that can recognize human speech, or have travelled through an airport immigration queue using image-recognition technology. Self-driving cars and automated flying drones are now in the testing stage before anticipated widespread use, while for certain learning and memory tasks, machines now outperform humans. Watson, an artificially intelligent computer system, beat the best human candidates at the quiz game Jeopardy.
Artificial intelligence, in contrast to normal hardware and software, enables a machine to perceive and respond to its changing environment. Emergent AI takes this a step further, with progress arising from machines that learn automatically by assimilating large volumes of information. An example is NELL, the Never-Ending Language Learning project from Carnegie Mellon University, a computer system that not only reads facts by crawling through hundreds of millions of web pages, but attempts to improve its reading and understanding competence in the process in order to perform better in the future.
Like next-generation robotics, improved AI will lead to significant productivity advances as machines take over – and even perform better – at certain tasks than humans. There is substantial evidence that self-driving cars will reduce collisions, and resulting deaths and injuries, from road transport, as machines avoid human errors, lapses in concentration and defects in sight, among other problems. Intelligent machines, having faster access to a much larger store of information, and able to respond without human emotional biases, might also perform better than medical professionals in diagnosing diseases. The Watson system is now being deployed in oncology to assist in diagnosis and personalized, evidence-based treatment options for cancer patients.
Long the stuff of dystopian sci-fi nightmares, AI clearly comes with risks – the most obvious being that super-intelligent machines might one day overcome and enslave humans. This risk, while still decades away, is taken increasingly seriously by experts, many of whom signed an open letter coordinated by the Future of Life Institute in January 2015 to direct the future of AI away from potential pitfalls. More prosaically, economic changes prompted by intelligent computers replacing human workers may exacerbate social inequalities and threaten existing jobs. For example, automated drones may replace most human delivery drivers, and self-driven short-hire vehicles could make taxis increasingly redundant.
On the other hand, emergent AI may make attributes that are still exclusively human – creativity, emotions, interpersonal relationships – more clearly valued. As machines grow in human intelligence, this technology will increasingly challenge our view of what it means to be human, as well as the risks and benefits posed by the rapidly closing gap between man and machine.
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Tuesday, 11 August 2015

Special Issue For Image Processing



Best 25 papers will be published online.Participate in this special issue and get a chance to win the Best Paper Award for Image Processing. Also other authors will have special prizes to be won.

What is Image Processing?
Image processing is a method to convert an image into digital form and perform some operations on it, in order to get an enhanced image or to extract some useful information from it. It is a type of signal dispensation in which input is image, like video frame or photograph and output may be image or characteristics associated with that image. Usually Image Processingsystem includes treating images as two dimensional signals while applying already set signal processing methods to them. 
It is among rapidly growing technologies today, with its applications in various aspects of a business. Image Processing forms core research area within engineering and computer science disciplines too.Image processing usually refers to digital image processing, but optical and analog image processing also are possible.
Analog or visual techniques of image processing can be used for the hard copies like printouts and photographs. Image analysts use various fundamentals of interpretation while using these visual techniques. The image processing is not just confined to area that has to be studied but on knowledge of analyst. Association is another important tool in image processing through visual techniques. So analysts apply a combination of personal knowledge and collateral data to image processing.
Digital Processing techniques help in manipulation of the digital images by using computers. As raw data from imaging sensors from satellite platform contains deficiencies. To get over such flaws and to get originality of information, it has to undergo various phases of processing. The three general phases that all types of data have to undergo while using digital technique are Pre- processing, enhancement and display, information extraction.
If you have worked on any part of image processing prepare a research paper and submit to us
Image processing basically includes the following three steps.
  • Importing the image with optical scanner or by digital photography.The acquisition of images (producing the input image in the first place) is referred to as imaging.
  • Analyzing and manipulating the image which includes data compression and image enhancement and spotting patterns that are not to human eyes like satellite photographs.
  • Output is the last stage in which result can be altered image or report that is based on image analysis.

Purpose of Image processing
The purpose of image processing is divided into various groups. They are:
  • Visualization - Observe the objects that are not visible.
  • Image sharpening and restoration - To create a better image.
  • Image retrieval - Seek for the image of interest.
  • Measurement of pattern – Measures various objects in an image.
  • Image Recognition – Distinguish the objects in an image.

Applications of Image processing
Image processing has been an important stream of Research for various fields. Some of the application areas of Image processing are….
Intelligent Transportation Systems – E.g. Automatic Number Plate Recognition, Traffic Sign Recognition
Remote Sensing –E.g.Imaging of earth surfaces using multi Spectral Scanners/Cameras, Techniques to interpret captured images etc.
Object Tracking – E.g. Automated Guided Vehicles, Motion based Tracking, Object Recognition
 Defense surveillance – E.g. Analysis of Spatial Images, Object Distribution Pattern Analysis of Various wings of defense. Earth Imaging using UAV etc.
 Biomedical Imaging & Analysis – E.g. Various Imaging using X- ray, Ultrasound, computer aided tomography (CT) etc. Disease Prediction using acquired images, Digital mammograms.etc.
Automatic Visual Inspection System – E.g.Automatic inspection of incandescent lamp filaments, Automatic surface inspection systems,    Faulty component identification etc.
And many other applications…..
To contribute your research work in Image processing please prepare an article on it and submit to us. 

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