Showing papers by "Velagapudi Ramakrishna Siddhartha Engineering College published in 2007"

Tensile properties of elephant grass fiber reinforced polyester composites

Abstract: Elephant grass stalk fibers were extracted using retting and chemical (NaOH) extraction processes. These fibers were treated with KMnO4 solution to improve adhesion with matrix. The resulting fibers were incorporated in a polyester matrix and the tensile properties of fiber and composite were determined. The fibers extracted by retting process have a tensile strength of 185 MPa, modulus of 7.4 GPa and an effective density of 817.53 kg/m3. The tensile strength and modulus of chemically extracted elephant grass fibers have increased by 58 and 41%, respectively. After the treatment the tensile strength and modulus of the fiber extracted by retting have decreased by 19, 12% and those of chemically extracted fiber have decreased by 19 and 16%, respectively. The composites were formulated up to a maximum of 31% volume of fiber resulting in a tensile strength of 80.55 MPa and tensile modulus of 1.52 GPa for elephant grass fibers extracted by retting. The tensile strength and the modulus of chemically extracted elephant grass fiber composites have increased by approximately 1.45 times to those of elephant grass fiber composite extracted by retting. The tensile strength of treated fiber composites has decreased and the tensile modulus has shown a mixed trend for the fibers extracted by both the processes. Quantitative results from this study will be useful for further and more accurate design of elephant grass fiber reinforced composite materials.

Design of Microstrip Antennas Using Artificial Neural Networks

Abstract: A general design procedure is suggested for the micro strip antennas using artificial neural networks and this is demonstrated using the rectangular patch geometry. In the design procedure, synthesis and analysis are defined as forward side and reverse side of the problem.

Identification of Non-Black Inks Using HSV Colour Space

Abstract: An important problem in questioned document examination is detection of alterations done by inserting words or additional lines of text. In this paper, we present a statistical pattern recognition driven approach that views it as a two- class problem. Given two sample words, one of which is a suspected alteration, it is necessary to determine if the two belong to the same class or different classes. Our approach is defined in two stages. We start with a 11-dimensional vector that comprises colour features defined in HSV space and texture features. During the training phase, we derive within-class and between-class LI distance distributions and identify an optimal threshold that minimizes Type I and Type II errors. During the second or test phase, we take a pair of unkown samples and use the threshold value obtained from the training phase to decide if the two belong to the same class or distinct classes. Our experimental results involving more than 95000 pairs of word images show that the approach gives an accuracy of over 90% for gel and roller pens and an accuracy of 85% for ball pen writings.

Analytical prediction of forced convective heat transfer of fluids embedded with nanostructured materials (nanofluids)

Abstract: Nanofluids are a new class of heat transfer fluids developed by suspending nanosized solid particles in liquids. Larger thermal conductivity of solid particles compared to the base fluid such as water, ethylene glycol, engine oil etc. significantly enhances their thermal properties. Several phenomenological models have been proposed to explain the anomalous heat transfer enhancement in nanofluids. This paper presents a systematic literature survey to exploit the characteristics of nanofluids, viz., thermal conductivity, specific heat and other thermal properties. An empirical correlation for the thermal conductivity of Al2O3 + water and Cu + water nanofluids, considering the effects of temperature, volume fraction and size of the nanoparticle is developed and presented. A correlation for the evaluation of Nusselt number is also developed and presented and compared in graphical form. This enhanced thermophysical and heat transfer characteristics make fluids embedded with nanomaterials as excellent candidates for future applications.

A Novel Approach to Medical Image Compression Using Sequential 3D DCT

Abstract: The output of recently developed imaging devices is more often in a digital format and both storage space and transmission times of these images profit from data compression. In this paper a novel approach to medical image compression based on three-dimensional Discrete Cosine Transformation (DCT) is proposed. The basic idea is to de-correlate similar pixel blocks through three-dimensional DCT transformation. A number of adjacent pixel blocks are grouped together to form a three-dimensional data cube. Each data cube is 3D DCT transformed, quantized, and Entropy coded (using Variable length coding scheme-Huffman coding scheme). An experimental result says that the new approach is effective specifically for medical images.