Original Engineering Software for Composite Materials Modelling on a Smartphone Device
- 1 Faculty of Engineering, Lebanese University, Beirut, Lebanon
- 2 Faculty of Engineering, Lebanese University, Beirut, Lebanon
- 3 LASMIS, University of Technology of Troyes, Troyes, France
Abstract
The increasing demand for mobile simulation tools has opened new possibilities in engineering applications, particularly in composite material modelling. This paper introduces original engineering software developed to simulate composite materials on smartphones. The research explores the capabilities of mobile devices to perform simulations that are traditionally confined to desktop systems. Key challenges, such as computational limitations and the optimization of software architecture, now with integrated quantitative performance metrics such as computation time, accuracy, and memory efficiency, are addressed through the use of finite element analysis (FEA) and other advanced numerical methods. The software utilizes HTML-based coding for cross-platform accessibility, allowing engineers and researchers to conduct simulations anytime, anywhere. Strategies like parallel processing, cloud-assisted computation, and algorithmic optimization were implemented to enhance performance. The software’s real-time feedback and adaptive modelling provide accurate simulations of composite materials such as fiber-reinforced polymers. Furthermore, this paper reviews existing mobile-based simulation tools, highlighting their strengths and areas for improvement, while proposing novel solutions to increase efficiency, accuracy, and usability. The findings demonstrate that mobile devices, with optimized software, can successfully handle complex simulations, democratizing access to advanced engineering tools.
- Ghlaim, K.H. (2024) Woven Factor for the Mechancial Properties of Woven Composite Materials. Journal of Engineering , 16, 6012-6027. https://doi.org/10.31026/j.eng.2010.04.22
- Hull, D. and Clyne, T.W. (1996) Frontmatter. In: An Introduction to Composite Materials , Cambridge Solid State Science Series , Cambridge University Press, 1-6.
- Shadish, W., Cook, T. and Campbell, D. (2004) Quasi-Experimental Designs for Generalized Causal Inference.
- Sultan, M.S., Khan, M.A., Khan, H. and Ahmad, B. (2022) Pathways to Strengthening Capabilities: A Case for the Adoption of Climate-Smart Agriculture in Pakistan. APN Science Bulletin , 12, 171-183. https://doi.org/10.30852/sb.2022.2021
- Nielsen, J. (2012) Usability 101: Introduction to Usability. Nielsen Norman Group.
- Mallett, R.D.C., Stroeve, J.C., Tsamados, M., Landy, J.C., Willatt, R., Nandan, V., et al . (2021) Faster Decline and Higher Variability in the Sea Ice Thickness of the Marginal Arctic Seas When Accounting for Dynamic Snow Cover. The Cryosphere , 15, 2429-2450. https://doi.org/10.5194/tc-15-2429-2021
- Akindote, O.J., Adegbite, A.O., Dawodu, S.O., et al . (2023) Innovation in Data Storage Technologies: From Cloud Computing to Edge Computing. Computer Science & IT Research Journal , 4, 273-299. https://doi.org/10.51594/csitrj.v4i3.661
- Es-haghi, M.S., Anitescu, C. and Rabczuk, T. (2024) Methods for Enabling Real-Time Analysis in Digital Twins: A Literature Review. Computers & Structures , 297, Article 107342. https://doi.org/10.1016/j.compstruc.2024.107342
- ANSYS Inc (2024) ANSYS Composite PrepPost: Comprehensive Analysis for Composite Structures.
- Daniel, I.M. and Ishai, O. (2006) Engineering Mechanics of Composite Materials. Oxford University Press.
- Altair Engineering (2024) OptiStruct: The Industry-Leading Solution for Structural Optimization.
- Altair Engineering (2024) Classical Laminate Theory for Composite Design.
- MSC Software Corporation (2024). Nastran and Patran: Leading Simulation Tools for Aerospace and Automotive.
- MSC Software Corporation (2024) Finite Element Analysis in Aerospace Composites.
- Dassault Systèmes (2024) Abaqus FEA: Nonlinear and Dynamic Material Simulation.
- Lemaitre, J. (1996) A Course on Damage Mechanics. Springer.