P A College of Engineering

About: P A College of Engineering is a based out in . It is known for research contribution in the topics: Dihedral angle & Ring (chemistry). The organization has 298 authors who have published 594 publications receiving 4888 citations.

Influence of ZnO nanoparticles on thermophysical and tribological properties of polyolester oil

Abstract: An experimental assessment of thermo-physical, tribological, and eco-friendly properties of polyolester (POE) oil with zinc oxide (ZnO) nanoparticles for use as nanolubricant in refrigeration compressor. The ZnO nanolubricants were added in the mass fractions in the range from 0.1% to 0.5%, at the temperatures of 0 °C, 20 °C, 30 °C, 40 °C, and 60 °C. The thermophysical properties include thermal conductivity, kinematic viscosity, flash point, fire point, pour point, and cloud point with respect to various proportions. The morphology and size of ZnO nanoparticles are studied using the scanning electron microscope test. The tests findings suggest that ZnO nanoparticles greatly improved the friction characteristics of pure POE oil. The addition of the concentration decreases the pour point by 13.6%; at the same time, the flashpoint is improved by 3.5% when the POE oil is blended with ZnO. Zinc oxide nanoparticles could improve the refrigerants’ performance by extending life and avoiding friction problems. The optimum ZnO content of nanolubricants is, therefore, 0.3% for the POE/ZnO nanoparticles addition. The COF values are reduced by 6.95% at the optimum concentration over that with POE oil. The nanoparticles’ addition up to 0.3% results in less wear as they provide a defensive film between the surfaces during their motion. The mass loss value increased due to the aggregation of ZnO nanoparticles. The higher thermal conductivity is obtained for the 0.3% volume fraction of nanoparticles, and other 0.1% and 0.5% volume fractions lesser.

Elimination of Hazard Cadmium Ions from Simulated Groundwater Using Hydroxyapatite Coated Filter Cake Made of Sewage Sludge and Cement Kiln Dust

Abstract: Novel sorbent named “coated filter cake by hydroxyapatite (CFCHAP)” that prepared from precipitation of hydroxyapatite nanoparticles on the filter cake was applied in permeable reactive barrier (PRB) technique. This barrier was tested by identification of its capability in the reclamation of simulated groundwater contaminated by cadmium ions. The filter cake is the material remaining from cement kiln dust and sewage sludge after calcium and phosphate extraction for manufacture of hydroxyapatite, respectively. Isotherm studies for CFCHAP–Cd interaction elucidated that Langmuir model is a suitable expression for representation of sorption measurements with determination coefficient (R2) > 0.99. The highest capacity of adsorption (qm) of CFCHAP is 34.722 mg/g which decreased slightly to 32.610 mg/g for mixture of 90% CFCHAP and 10% filter sand. The percentages of this mixture are suitable to fulfill the PRB requirements represented by acceptable hydraulic conductivity and reactivity in the continuous tests. As a function of the time, the experiments demonstrated a positive correlation between the longevity of the packed beds with the thickness of the PRB due to saturation with metal ions. The computerized solution by COMSOL 3.5a (2008) exhibited a good ability in describing the transportation of cadmium ions compared with experimental measurements. Measurements with model predictions signified that the cadmium propagation can be slowed at lower inlet concentration and water discharge for certain point along the bed.

Iris Recognition Using Segmental Euclidean Distances

Abstract: A novel segmentation method is developed for segmenting an Iris image into 6 circular segments after it has been cropped from an eye. Each segment is treated as a separate image to find Eigeniris and to recognize the Iris by the segmental Euclidean distance between the features of training and test samples computed from their segments. In addition to the Eigen features, the DCT and fuzzy features are extracted from the segments of iris images. Instead of segmental Euclidean distance as a classifier, the Support Vector Machine is also employed for the classification. The evaluation of performance on the CASIA V.2 database using Eigen, DCT and fuzzy features has resulted in the recognition rates of 93%, 98% and 95% respectively.

3D Face recognition using significant point based SULD descriptor

Abstract: In this work, we present a new 3D face recognition method based on Speeded-Up Local Descriptor (SULD) of significant points extracted from the range images of faces. The proposed model consists of a method for extracting distinctive invariant features from range images of faces that can be used to perform reliable matching between different poses of range images of faces. For a given 3D face scan, range images are computed and the potential interest points are identified by searching at all scales. Based on the stability of the interest point, significant points are extracted. For each significant point we compute the SULD descriptor which consists of vector made of values from the convolved Haar wavelet responses located on concentric circles centred on the significant point, and where the amount of Gaussian smoothing is proportional to the radii of the circles. Experimental results show that the newly proposed method provides higher recognition rate compared to other existing contemporary models developed for 3D face recognition.