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Malaysian pineapple (Yankee) leaf fiber composites damage investigation using non-destructive techniques


Najeeb, Muhammad Imran (2022) Malaysian pineapple (Yankee) leaf fiber composites damage investigation using non-destructive techniques. Doctoral thesis, Universiti Putra Malaysia.


In Malaysia, there are abundant agricultural wastes generated from 15,000 hectares of pineapple plantation. The current study focuses on fully utilising the pineapple leaf fiber (PALF) extracted from the Yankee variant sourced from a plantation in Telok Panglima Garang as a reinforcement material in composite, hence converting the agriculture waste into a potentially useful and sustainable resource. The physical, chemical, thermal, as well as mechanical properties of untreated and silane treated PALF were investigated in this study. Three types of composites, pineapple leaf fiber composite (P), pineapple leaf fiber/glass fiber composite (GPG), glass fiber composite (GGGG) were evaluated for low velocity impact (LVI) properties. Visual inspection, computed tomography (CT) scan, digital detector array (DDA) radiography and infrared (IR) thermography techniques were applied to detect the damage evolution of the impacted composites. The broad peaks at 1317.81 and 1100 cm-1 of the Attenuated Total Reflectance (ATR) analytical graph indicate silane compound bonding with PALF. In addition, there are no significant changes to the configuration of the silane’s treated PALF due to its crystallinity. Treated PALF displays thermal stability improvement by 5.9%, with degradation occurring at the temperature of 360°C. The surface area of the treated PALF displays broader peaks, indicating greater surface roughness compared to untreated PALF. The tensile strength test on single fiber shows PALF display highest tensile strength when treated for three hours compared to one and five hours respectively. The untreated PALF composite (UT-PALFC) possess 7.1% higher storage modulus than treated PALF composite (T-PALFC), indicating untreated fiber attribute to high dynamic property in composite. Meanwhile, the thermomechanical analysis shows the sequence of linear coefficient of thermal expansion (CTE) of the treated and untreated fiber composites as follows: T-PALFC > Neat epoxy > UT-PALFC. On the other hand, the low impact analysis shows three varying impact energy ranges at 1-2J, 2-9J and 9-12J for P, GPG, GGGG respectively. The addition of glass fiber in GPG composites further delayed damage initiation time and propagation throughout the sample by about 8.5% compared to GGGG composite as shown in LVI. Visual inspections as captured in photographic images show different damage modes in the presence of woven fiberglass mat in GPG compared to P. CT-scan images show significant cross-section cracks on impacted GPG and GGGG composites compared to P. Compared to IR thermography technique that only shows the general area of damage, the DDA radiography captures significant surface damages on impacted P, GPG and GGGG composites. For example, the DDA captures significant damage in GPG at 9J with an area of 84% less than IR thermography. However, CT-scan, DDA radiography and IR thermography failed to capture occurrence of surface delamination as observed in visual inspection. This shows that the NDT techniques used in this research need to be complimented with other tools for clearer interpretation of the extent impacted damage in composite. Overall, the newly developed hybrid GPG composite shows great potential in structural applications such as drone because of its favourable impact resistance properties.

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Additional Metadata

Item Type: Thesis (Doctoral)
Subject: Plant fiber - Malaysia
Subject: Nondestructive testing
Subject: Pineapple
Call Number: FK 2022 84
Chairman Supervisor: Prof. Ir. Ts. Mohamed Thariq Bin Haji Hameed Sultan, PhD, PEng, CEng, PTech
Divisions: Faculty of Engineering
Depositing User: Ms. Rohana Alias
Date Deposited: 19 Jun 2023 23:38
Last Modified: 19 Jun 2023 23:38
URI: http://psasir.upm.edu.my/id/eprint/103950
Statistic Details: View Download Statistic

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