Alias, Norma and Hamlan, Hazidatul Akma and Yusniman, Noorazura Shahira (2020) Parallel performance evaluation for curing process of thermoset nanocomposites materials. In: 2020 International Conference on the Science and Technology of Advanced Materials, STAM 2020, 20 November 2019 - 21 November 2019, New Delhi, India.
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Official URL: http://dx.doi.org/10.1016/j.matpr.2020.02.038
Abstract
The investigation towards rate of growth for the curing process of thermoset nanocomposites materials is of great concern to most engineering and chemistry researchers since it is closely related to our natural resources, and has valuable properties. It is important to tailor and control the waste composite materials temperature profile during curing process to reproduce and improve its efficiency. Due to this phenomenon, temperature profile during curing process between two layers of composite materials is considered in this study. The mathematical model of 1D convection-diffusion of the heat equation of thick thermoset composite during its curing process has been employed. We predicted the temperature behavior for separating two layers of nanocomposites materials. Mathematical modelling to represent the problem were discretized numerically by employing central Finite Different Method (FDM) with weight parameter h. The Linear System Equation (LSE) resulted from the discretization are solved by three numerical methods, Alternating Group Explicit (AGE), Red Black Gauss Seidel (RBGS) and Jacobi (JB). Results acquired from RBGS and JB methods have become the benchmarks for evaluating the results from AGE methods. Then, we developed parallel algorithms on the mathematical model based on AGE, RBGS and JB methods. Finally, we evaluated and analyzed the performance indicators based on the parallel performance evaluation (PPE) in solving the PDE. Parallel algorithm is computed in Parallel Virtual Machine (PVM) programming on Linux operating system (Fedora 21) as a platform in order to accelerate the sequential execution as well as the convergence rate. Parallel AGE has significantly outperformed their counterparts compared with the benchmark classical methods (RBGS and JB) for two dimensional problems. Despite having huge computational complexity, results obtained from Parallel AGE methods have proven valuable since it enables to provide solution with higher accuracy and stability.
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | finite different method, nanocomposites materials, parallel virtual 122 machine (PVM), temperature profile and parallel algorithm |
Subjects: | Q Science > QA Mathematics |
Divisions: | Science |
ID Code: | 93746 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 31 Dec 2021 08:48 |
Last Modified: | 31 Dec 2021 08:48 |
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