Investigation of fibre reinforced shape memory polymer composites for structural components

PhD Thesis


Emmanuel Kotikawattege Don, Chris. 2023. Investigation of fibre reinforced shape memory polymer composites for structural components. PhD Thesis Doctor of Philosophy (DPHD). University of Southern Queensland. https://doi.org/10.26192/yzvvq
Title

Investigation of fibre reinforced shape memory polymer composites for structural components

TypePhD Thesis
AuthorsEmmanuel Kotikawattege Don, Chris
Supervisor
1. FirstA/Pr Jayantha Epaarachchi
2. SecondProf Thiru Aravinthan
Institution of OriginUniversity of Southern Queensland
Qualification NameDoctor of Philosophy (DPHD)
Number of Pages231
Year2023
PublisherUniversity of Southern Queensland
Place of PublicationAustralia
Digital Object Identifier (DOI)https://doi.org/10.26192/yzvvq
Abstract

Shape memory polymers (SMPs), comprising a distinctive shape memorizing capability, is a significant and evolving branch of smart polymers. Shape memory polymer composites (SMPCs) were developed by reinforcing the SMP matrix to improve the inherently weak mechanical properties and durability of SMPs. General polymer composites have become a successful substitute construction material. Similarly, with both the structural performance and shape memory effect (SME), SMPCs will be ideal candidates to remedy the challenges of futuristic construction techniques. Specifically, SMPCs can be used effectively in prefabricated modular constructions, curved beams and other civil infrastructures to overcome drawbacks associated with the high requirements of labour, time and cost. This research aimed to develop circular and square hollow sectioned (CHS and SHS) structural SMPC components for the construction industry. E-glass, carbon and natural basalt fibres were integrated as reinforcements. The thermomechanical, mechanical, shape memory and programming damage characteristics were evaluated to analyse material performance. The SMPC structural sections were fabricated with a specially designed mould and the SME, damage predictions, structural performance and proof of concept were analysed. The durability of SMPCs was also investigated; mainly in terms of behaviour under fire, smoke generation, thermal decomposition, volatile gas characterisation, fatigue, moisture and elevated temperatures. Importantly, this thesis presents a firsthand, indepth programming damage analysis framework to fill knowledge gaps in the SMPC research field by linking experimental outcomes with viscoelastic FEA studies. Overall, this study established a comprehensive and wellrounded SMPC design outline to develop SMPC structural sections for civil constructions for the first time. The outcomes of this thesis will guide engineers to revolutionize well established construction methods and technologies, and provide innovative solutions to make civil constructions smarter, faster and cheaper.

Keywordsshape memory polymer composites; Durability; smart materials; Deployable structures
Related Output
Has partThermomechanical and fire performance of DGEBA based shape memory polymer composites for constructions
Has partDamage onset analysis of optimized shape memory polymer composites during programming into curved shapes
Has partShape memory polymer composite circular and square hollow members for deployable structures
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020401602. Composite and hybrid materials
401605. Functional materials
401609. Polymers and plastics
400505. Construction materials
400101. Aerospace materials
Public Notes

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Byline AffiliationsSchool of Engineering
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Related outputs

Shape memory polymer composite circular and square hollow members for deployable structures
Emmanuel, K.D.C., Jeewantha, L.H.J., Herath, H.M.C.M., Epaarachchi, J.A. and Aravinthan, T.. 2023. "Shape memory polymer composite circular and square hollow members for deployable structures ." Composites Part A: Applied Science and Manufacturing. 171. https://doi.org/10.1016/j.compositesa.2023.107559
Damage onset analysis of optimized shape memory polymer composites during programming into curved shapes
Emmanuel, K. D. C., Jeewantha, L. H. J., Herath, H. M. C. M., Epaarachchi, J. A. and Aravinthan, T.. 2022. "Damage onset analysis of optimized shape memory polymer composites during programming into curved shapes." Materialia. 26, pp. 1-11. https://doi.org/10.1016/j.mtla.2022.101599
Shape memory polymer smart plaster for orthopaedic treatments
Jeewantha, Janitha, Jayalath, Sandaruwan, Emmanuel, Chris, Herath, Madhubhashitha, Forster, Elizabeth, Islam, Mainul, Leng, Jinsong and Epaarachchi, Jayantha. 2022. "Shape memory polymer smart plaster for orthopaedic treatments." Smart Materials and Structures. 31 (11), pp. 1-14. https://doi.org/10.1088/1361-665X/ac943b
Distributed sensing based real-time process monitoring of shape memory polymer components
Herath, Madhubhashitha, Emmanuel, Chris, Jeewantha, Janitha, Epaarachchi, Jayantha and Leng, Jinsong. 2022. "Distributed sensing based real-time process monitoring of shape memory polymer components." Journal of Applied Polymer Science. 139 (22). https://doi.org/10.1002/app.52247
Investigation of curing kinetics and internal strains to enhance performances of bisphenol A based shape memory polymers
Jeewantha, L. H. J., Emmanuel, K. D. C., Herath, H. M. C. M., Epaarachchi, J. A., Islam, M. M. and Leng, J.. 2022. "Investigation of curing kinetics and internal strains to enhance performances of bisphenol A based shape memory polymers." Materialia. 21. https://doi.org/10.1016/j.mtla.2021.101264
In-situ performance evaluation of large shape memory polymer components via distributed optical fibre sensors
Herath, Madhubhashitha, Emmanuel, Chris, Epaarachchi, Jayantha and Jeewantha, Janitha. 2021. "In-situ performance evaluation of large shape memory polymer components via distributed optical fibre sensors." 10th International Conference on Information and Automation for Sustainability (ICIAfS 2021). Negambo, Sri Lanka 11 - 13 Aug 2021 United States. https://doi.org/10.1109/ICIAfS52090.2021.9605868
Development and characterization of shape memory polymers for non-invasive biomedical applications
Jeewantha, Janitha, Emmanuel, Chris, Herath, Madhubhashitha, Islam, Mainul and Epaarachchi, Jayantha. 2021. "Development and characterization of shape memory polymers for non-invasive biomedical applications." ASME 2021 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS2021). United States and Online New York, United States. https://doi.org/10.1115/SMASIS2021-66024
Multi-attribute parametric optimisation of shape memory polymer properties for adaptive orthopaedic plasters
Jeewantha, L. H. J., Emmanuel, K. D. C., Herath, H. M. C. M., Islam, M. M., Fang, L. and Epaarachchi, J. A.. 2022. "Multi-attribute parametric optimisation of shape memory polymer properties for adaptive orthopaedic plasters." Materialia. 21, pp. 1-12. https://doi.org/10.1016/j.mtla.2022.101325
Thermomechanical and fire performance of DGEBA based shape memory polymer composites for constructions
Emmanuel, K. D. C., Herath, H. M. C. M., Jeewantha, L. H. J., Epaarachchi, J. A. and Aravinthan, T.. 2021. "Thermomechanical and fire performance of DGEBA based shape memory polymer composites for constructions." Construction and Building Materials. 303. https://doi.org/10.1016/j.conbuildmat.2021.124442