ABSTRACT
Wood is a cellulosic material that is most abundantly available in nature. Wood has been extensively used as reinforcement in polymer composite materials. Wood polymer composite (WPC) is an environmentally friendly and sustainable material exploited in building and construction within the marine, packaging, housewares, aerospace, and automotive industries. However, the precision of testing equipment for finding the properties of WPCs becomes less feasible compared to experimental analysis due to a high degree of differences in the measurement of properties such as stress, strain and deformation. Thus, evaluating the mechanical properties of WPCs using finite element analysis (FEA) can aid in overcoming the inadequacies in measuring physical properties prior to experimental analyses. Furthermore, the prediction of mechanical properties using simulation tools has evolved to analyze novel material performance under various conditions. The current study aimed to examine the mechanical properties of saw dust-reinforced recycled polypropylene (rPP) through experimentation and FEA. A model was developed using SolidWorks, and simulation was performed in ANSYS to predict the mechanical properties of the WPCs. To validate the obtained results, the simulated static tension test results were confirmed with experimental tension tests, and both assessments were well in accordance with each other. Using FEA to predict material properties could be a cost-effective technique in studying new materials under varied load conditions.
ABSTRACT
This study was conducted to set up a new reference line for municipal solid waste quantification and characterization in the least urbanized cities of a developing nation. A survey was run to collect baseline data from 60 new municipalities of Nepal. The study covered a sample size of 3300 households, 600 institutions and 600 commercial establishments in those municipalities. The municipalities were further stratified according to geographical location, the degree of urbanization, household expenditure and population size to assess the influence on waste generation. The results indicated that the average per capita household waste generation is 115 g day-1 while the average total municipal waste generation was estimated to be 180 g day-1 per capita.The study also revealed that size of municipal population, geographic location, household expenditure and degree of urbanization were found to have a significant influence on the unit waste generation. The larger the size of municipal population the higher the per capita household waste generation, degree of urbanization and per capita waste production. Increasing household expenditure revealed an increase in the unit waste generation. The waste categories included organic waste, plastics, paper and paper products, textiles, rubber and leather, metals, glass, and others. The results indicated that organic waste dominated the characterization (62%), followed by plastics (12%) and paper/paper products (11%).