Repurposing Plastic Wastes in Non-conventional Engineered Wood Building Bricks for Constructional Application - A Mechanical Characterization using Experimental and Statistical Analysis

Balakrishna S. Maddodi, U. A. Lathashri, Sonal Devesh, Asha Udaya Rao, B. Gowri Shenoy, Heshan Thenuka Wijerathne Jayawardane, Nilakshman Sooriyaperkasam, M. Prasanna Kumar

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)

Abstract

Plastic waste is accumulating at an alarming rate, polluting the environment due to various industrial activities. Plastic waste is also non-biodegradable, making global accumulation deteriorating. Moreover, it is observed that using sustainable building materials encourages the efficient use of wood industry waste. The study uses polyethylene terephthalate (PET) waste combined with wood fibers to make the non-conventional bricks. In the present study, two distinct types of bricks were evaluated, one containing 25% by weight of PET waste and the other containing 40%. All samples were subjected to compressive strength and hardness tests in accordance with the applicable American Society for Testing and Materials (ASTM) standards. Since a perfect brick composition should include both the mechanical properties on the higher sides, in the current work, Data Envelopment Analysis (DEA) was utilized to conduct a multi-response analysis and determine the optimal combination of plastic waste and wood fibers for manufacturing non-conventional bricks. The brick containing 25% by weight of plastic waste proved to be the best of the two types of wood plastic composites (WPCs) created in this study, with a grey relational grade value ranging between 2.384 and 3.045.

Original languageEnglish
Pages (from-to)329-336
Number of pages8
JournalEngineered Science
Volume18
DOIs
Publication statusPublished - 2022

All Science Journal Classification (ASJC) codes

  • General Engineering
  • Physical and Theoretical Chemistry
  • Chemistry (miscellaneous)
  • General Materials Science
  • Energy Engineering and Power Technology
  • Artificial Intelligence
  • Applied Mathematics

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