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DC Field | Value | Language |
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dc.contributor.author | Srihari, Palli | - |
dc.date.accessioned | 2014-12-04T12:32:41Z | - |
dc.date.available | 2014-12-04T12:32:41Z | - |
dc.date.issued | 2005 | - |
dc.identifier | M.Tech | en_US |
dc.identifier.uri | http://hdl.handle.net/123456789/13055 | - |
dc.guide | Pandey, A. D. | - |
dc.description.abstract | The most spectacular developments railway tracks went through since the beginning of the railways can be seen in the improvement of their fastening systems. The most important function of fastening systems is to provide strong and flexible connection between rail and its supporting structure i.e. the sleeper. The pre-stressed concrete sleepers use Spheroidal Graphite Cast Iron (SGCI) inserts together with Elastic Rail Clip and rubber/elastomeric pad to hold the rails. As there are four SGCI inserts embedded in a normal single/mono-block pre-stressed concrete sleeper, reducing the weight of the insert is necessary both from the economical point of view as well as design point of view. The present work is concentrated on optimizing the design of this insert, considering various geometric parameters used in its design by reducing its volume which is in direct proportion to its weight. The model of the insert has been built parametrically to carry the design optimization process with ease and efficiency. Stress analysis of the insert alone, and when the insert is embedded in the sleeper has been carried out. Three effective load cases where the insert is subjected to maximum loads under the ideal operating conditions are considered for the stress analysis and optimization. An algorithmic optimization of the SGCI insert model has been done using the Design optimization tool in ANSYS considering the geometric parameters as design variables and volume as the objective parameter. A comparison has been made between the results achieved by the algorithmic optimization and the results achieved by the limited parametric optimization using neural network. It is observed that target weight could not be achieved using neural network. It has been found that design variable `h' defining the height of the shaft/shank portion of the insert is more critical to the weight of the SGCI insert. The weight of the insert has been reduced from I.51 Kg to 1.38 Kg for the worst state of stresses occurring in the most effective load condition keeping the induced stresses within permissible limit. The studies conducted clearly indicate that reduction in weight of the SGCI insert is a distinct possibility, without compromising on the enhanced factors of safety associated with its functioning under normal operating conditions. | en_US |
dc.language.iso | en | en_US |
dc.subject | EARTHQUAKE ENGINEERING | en_US |
dc.subject | SGCI INSERT | en_US |
dc.subject | OPERATING CONDITIONS | en_US |
dc.subject | SPHEROIDAL GRAPHITE CAST IRON | en_US |
dc.title | OPTIMIZATION OF SGCI INSERT UNDER OPERATING CONDITIONS | en_US |
dc.type | M.Tech Dessertation | en_US |
dc.accession.number | G12317 | en_US |
Appears in Collections: | MASTERS' THESES (Earthquake Engg) |
Files in This Item:
File | Description | Size | Format | |
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G12317.pdf | 8.96 MB | Adobe PDF | View/Open |
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