Experimental Analysis for Optimizing Parameter Heating System

Authors(2) :-M. Sabaskar, Dr. K. Karthick

This suggest a better replacement of cold mass fraction which defines the ratio between the mass of air moving out through the cold exit to the actual mass of air entering the vortex tube through the inlet. Sustainable manufacturing Innovations elements are Remanufacture Redesign, Recover, Recycle, Reuse, Reduce. It has a good thermal response that restructures it with a low temperature. The properties of materials are particular to the exact composition of the metal and the way it was processed. The optimizing the parameters of vortex tube for increasing the cooling temperature. These optimized vortex tube could produce maximum hot gas temperature of 391 K at 1215% hot gas fraction and a minimum cold gas temperature of 267 K at about 60% cold gas fraction. CFD - a computational technology that enables one to study the dynamics of things that flow. CFD is concerned with numerical solution of differential equations governing transport of mass, momentum and energy in moving fluid. Cold air machining outperforms mist coolants and substantially increases tool life and feed rates on dry machining operations. The effective cooling from a Cold Air Gun can eliminate heat-related parts growth while improving parts tolerance and Surface finish quality Commercial vortex tubes are designed for industrial applications to produce a temperature drop of about 26.6 C (48 F). With no moving parts, no electricity, and no Freon, a vortex tube can produce refrigeration up to 6,000 BTU (6,300 kJ) using only filtered compressed air at 100 PSI (689 kPa). A control valve in the hot air exhaust adjusts temperatures, flows and refrigeration over a wide range.

Authors and Affiliations

M. Sabaskar
Post Graduates, Department of Mechanical Engineering, King College of Technology, Namakkal, Tamil Nadu, India
Dr. K. Karthick
Associate Professor, Department of Mechanical Engineering, King College of Technology, Nallur, Namakkal, Tamil Nadu, India

Computational Fluid Dynamics Analysis, Navier – Stokes Equations, SIMPLE, SIMPLE-C, SIMPLER, QUICK and PISO.

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Publication Details

Published in : Volume 4 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 496-500
Manuscript Number : IJSRSET1841114
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

M. Sabaskar, Dr. K. Karthick, " Experimental Analysis for Optimizing Parameter Heating System, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 1, pp.496-500, January-February-2018.
Journal URL : http://ijsrset.com/IJSRSET1841114

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Geo-additive Model in Small Area Estimation of Poverty

Authors(3) :-M. Sabaskar, Dr. K. KarthickNovi Hidayat Pusponegoro, Anik Djuraidah, Anwar Fitriyanto

Spatial data contains of observation and region information, can describes spatial patterns such as poverty. In poverty parameter estimation, the less of sample adequacy to deliver direct estimation is one of the limitation, thus Small Area Estimation (SAE) was developed to handle it. Since, the small area estimation techniques require “borrow strength” across the neighbor areas furthermore SAE was developed by integrating spatial information into the model, named as Spatial SAE. SAE and spatial SAE model require the fulfilment of covariate linearity assumption as well as the normality of the response distribution that is sometimes violated, and the geo-additive model offers those handling using the smoothing function. Therefore, the purpose of this paper is to compare the SAE, Spatial SAE and Geo-additive model in order to estimate, at sub-district level, mean per capita income of each areas using the poverty survey data in Bangka Belitung province at 2017 by the Institute of statistics. The findings of the paper are the Geo-additive is the best fit model based on AIC, and spatial information don't influence the estimation in SAE and spatial SAE model since they have the similar estimation performance.

EBLUP, spatial EBLUP, geo-additive, income per capita

Publication Details

Published in : Volume 4 | Issue 11 | November-December 2018
Date of Publication : 2018-11-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) :
Manuscript Number : IJSRSET1841114
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Novi Hidayat Pusponegoro, Anik Djuraidah, Anwar Fitriyanto, " Geo-additive Model in Small Area Estimation of Poverty, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 11, pp., November-December-2018.
Journal URL : http://ijsrset.com/IJSRSET1841114

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