Thermal response analysis and parameter prediction of additively manufactured polymers
Moslemi, Naved, Abdi, Behzad., Gohari, Soheil, Sudin, Izman, Atashpaz-Gargari, E., Redzuan, Norizah, Ayob, Amran, Burvill, Colin, Su, Meini and Arya, Farid (2022) Thermal response analysis and parameter prediction of additively manufactured polymers. Applied Thermal Engineering, 212. ISSN 13594311
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Farid Arya Article AAM.pdf - Accepted Version Available under License Creative Commons Attribution No Derivatives. Download (1MB) | Preview |
Abstract
Fused Deposition Modelling (FDM), is an additive manufacturing technology where polymers are extruded using appropriate processing parameters to achieve suitable bonding while ensuring that overheating does not occur. Among processing parameters, polymer inlet temperature, nozzle size, extrusion speed, and air cooling speed are significantly effect on the extrusion process at the distance between the build plate and the nozzle tip (standoff region). This study aims to evaluate the influences of the processing parameters on the thermal behavior and phase change zone of Polyamide 12 (PA12) and Acrylonitrile Butadiene Styrene (ABS) polymers at standoff region. A nonlinear three-dimensional (3D) finite element (FE) model was developed by implementing an apparent heat capacity model using the Heat Transfer Module in COMSOL® Multiphysics software. FE results in the standoff region were validated by experimental tests, concerning various nozzle sizes and extrusion speed. The validated numerical results demonstrated that there is a complex correlation between processing parameters and thermal behaviors such as phase change and temperature distribution in the standoff region. The FE results were then employed in training an artificial neural network (ANN). A well-established compromise between the trained ANN and the FE results demonstrates that the trained ANN can be employed in the prediction of further thermal and glass transition behavior using subsequent processing parameters.
| Item Type: | Article |
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| Additional Information: | N.M would like to acknowledge the funding received from UTM under the Post-Doctoral Fellowship Scheme (Grant. No. Q. J130000.21A2.05E30) for the Project: “Uniaxial and Biaxial Ratcheting of a Girth-Welded Super Duplex Stainless Steel (UNS S32750) Pressurized Pipe”. |
| Keywords: | Finite element analysis Artificial Neural Network Polymers Additive manufacturing 3D printing |
| Depositing User: | RED Unit Admin |
| Date Deposited: | 31 May 2022 09:25 |
| Last Modified: | 30 Jun 2024 03:00 |
| URI: | https://bnu.repository.guildhe.ac.uk/id/eprint/18526 |
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