Capillary Helix Tube Diameter Optimization Using Neural Network Tool
| Author(s) | : | Raj Kumar Bharti, Aanand Shukla |
| Institution | : | M. Tech. Scholar, Mechanical Department, Vindhya Institute of Technology & Science, Jabalpur, M.P |
| Published In | : | Vol. 3, Issue 9 — September 2016 |
| Page No. | : | 192-197 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
This investigation the model is made for to develop mathematical model to determine the flow characteristicsof refrigerant inside a straight/helix capillary tube for adiabatic flow conditions. A capillary tube designed anddeveloped to work with R22 was tested in literature Y Raja et. al. [4], and its performance using R152a is evaluated andcompared with its performance when R22 was used. Finally, the results of mathematical model are valuated with ANSYSCFX and suitable result is optimized using neural Network tool, which this results are found to be in fair agreement. It isobserved from the results dryness fraction by using the helical capillary tube (R152a refrigerant flow) is better thanstraight and existing helical capillary tube (R22 refrigerant flow). The best suitable helical coiled design is suggested.
Raj Kumar Bharti, Aanand Shukla, “Capillary Helix Tube Diameter Optimization Using Neural Network Tool”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 3, Issue 9, pp. 192-197, September 2016.
