返回
Repurposing plastic waste: Experimental study and predictive analysis using machine learning in bricks
DOI:10.1016/j.molstruc.2024.139158.png)
摘要
En 中文
The construction industry significantly contributes to environmental degradation and resource depletion. This paper investigates the use of waste plastic from post-consumer and post-industrial sources as a sustainable alternative in brick manufacturing. By substituting plastic waste for traditional materials like clay or cement, the ecological footprint of brick production is reduced, and plastic pollution is mitigated by diverting waste from landfills and oceans. This study employs dual approach of experimentation as well as machine learning for assessing the strength behaviour of bricks enhanced with plastic, emphasising compressive strength, durability, thermal insulation, and moisture resistance. Utilization of Chlorinated Polyvinyl Chloride (CPVC) for Waste plastic bricks (WPB) was done by replacing cement and sand in different proportions i.e. 10 %, 20 %, 30 %, 40 %, and 50 % of fly ash bricks The best performance was observed at 30 % replacement of sand with waste CPVC. A Deep Neural Network (DNN) model also predicted compressive strength and water absorption, identifying key material components influencing brick properties through SHAP value analysis. This combined experimental and predictive modelling approach demonstrates the potential of waste plastic in creating lightweight, sustainable building materials for structural applications, contributing to sustainable construction practices.
Keyword:
Solid waste management
Fly ash
Waste plastic
Compressive strength
XRD
Machine learning
Deep neural network
SHAP analysis
期刊
IF:
4.7
论文数:
3.6W
被引数:
6.6W
机构
引用论文
Durability Assessment and Microstructure of High-Strength Performance Bricks Produced from PET Waste and Foundry Sand
MATERIALS
IF3.2
Study of Metakaolinite Geopolymeric Mortar with Plastic Waste Replacing the Sand: Effects on the Mechanical Properties, Microstructure, and Efflorescence
MATERIALS
IF3.2

