FEASIBILITY STUDY ON THE EFFECT OF PET BOTTLE FIBRES IN CONCRETE
Journal: International Journal of Advanced Research (Vol.7, No. 1)Publication Date: 2019-02-01
Authors : Chimi Karma Tshering Darjay Karma S. Phuntsho Lhakpa W. Thingh Tamang Phuntsho Namgyal Tshering Wangmo Ugyen Wangchuk; Tshering Cheki.;
Page : 35-42
Keywords : Shredded PET bottle fibre Compressive strength Split tensile strength Flexural strength Percentage replacement of fine aggregate.;
Abstract
Plastics and plastic bottles are adjustable for any common use due to its properties like durability, light weight and its ability to be moulded, however it excessive production and use has become a serious man made a threat to the environment. Disposal of plastic wastes have not only degrade degrades land fertility and deteriorates a scenic value of the place but also threatens human health. Moreover, with exponential increment of construction activities taking place around the globe today, many engineers and real estate developers in the construction industries are facing challenges in acquiring raw materials like aggregates due to huge demand of concrete. The extraction of natural aggregates exploits a natural environment and disturbs aquatic life. Therefore, this study was carried out to reduce excessive extraction of natural aggregate and production of plastic waste by using waste PET bottles in concrete. This study have found that, maximum replacement of 1.25% of a natural fine aggregate by weight with shreddedPET bottles fulfills the compressive and flexural strength requirement.
Other Latest Articles
- A COMPLEMENTATION OF THE LABADA TEACHING MODEL FOR A GENDER SENSITIZED SOCIETY
- AN EMPIRICAL STUDY ON YOUTH PERCEPTION TOWARDS ENTREPRENEURSHIP WITH REFERENCE TO VIJAYAWADA CITY
- ASSESSMENT OF CYTO-MORPHOLOGICAL CHANGES IN EPITHELIAL ORAL MUCOSA AMONG SICKLE CELL ANEMIA PATIENTS ATTENDING MANAGIL PEDIATRIC TEACHING HOSPITAL, GEZIRA STATE ,SUDAN (2017)
- Pre-Diagnosis of Osteoporosis Using Probabilistic Neural Networks
- Prediction of the Force on a Projectile in an Electromagnetic Launcher Coil with Multilayer Neural Network
Last modified: 2019-02-20 18:35:05