•Municipal solid waste characterization study was conducted in Johannesburg.•Effect of seasonal variation was evaluated.•A forecast was conducted on the trend of the wastes generated.
The huge ...increase generation of municipal solid waste (MSW) has recently become an issue of global concern. This is because waste generation increases as the population increases and the management of this waste has equally become a bit difficult. This study aims at determining the characterization and the pattern of municipal solid waste (MSW) in the City of Johannesburg (CoJ), South Africa. The results revealed that plastics and organic wastes constitute the highest waste content in both the daily refuse (DR) and round collected refuse (RCR). The results further showed that DRs are 28% and 26% for plastic wastes, while 28% and 29% organic wastes accounted for the RCRs during the summer and winter seasons respectively. The carbon to nitrogen ratio (C:N) content of the food wastes employed in this study was evaluated to be 22.66 and the empirical equation generated was C27H44NO16. STATA 12 software and ANOVA statistical technique were used to evaluate the seasonal variation between the winter and summer seasons (spanning a space of six months). The p-values obtained for the DR was (p-value = 0.9775) and for the RCR, it was (p-value = 0.9760) at 95% confidence level using STATA 12 tests. Similarly, the p-value obtained for the DR was (p-value = 0.999) and for the RCR, it was (p-value = 0.991) in turn using ANOVA tests at 95% confidence level. Furthermore, Minitab software was used to forecast the trend of waste generation between 2016 and 2025. Based on the overall results, it was concluded that the differences between the wastes generated in both seasons were not statistically significant (p > 0.05). Furthermore, a total of 102,406 tonnes of wastes would be generated during the period under consideration (a period of ten years). This indicates a negative trend for CoJ in terms of waste generation. However, this trend can be mitigated through Zero waste (ZW) implementation.
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•Cost benefit analysis of a municipal solid waste recycling facility.•Internal Rate of Return and Net Present Value of a project.•MATLAB, Python and R-Studio for comparation and ...validation.
Rapid population and economic growth, changes in consumption pattern etc. have become major contributing factors to severe municipal solid waste generation globally. Thus, various methods are being employed to manage the incessant municipal solid waste generation for a sustainable solid waste management and one of the viable approaches is the recycling option. The main objective of this paper is to determine the cost benefit analysis of setting up a recycling facility for the processing of various wastes for use as raw materials by industries. The cost benefit analysis was carried out based on historic data obtained from the municipality and some recent waste composition data. The overall analysis was done using Excel software. From the Excel software analysis, Internal Rate of Return on investment was 42%, Internal Rate of Return on equity was 98% and Net Present Value was R 63, 420,000 (USD$ 4646225.33). In ascertaining the result obtained from the Microsoft Excel, three data analysis and technical computing software (MATLAB, Python, and R-Studio) were employed. This was necessary to compare and validate the cost-benefit indicators (Net Present Value and Internal Rate of Return). Besides, evaluating the performance of each software with regards to the cost-benefit evaluation is ideal for a recycling plant like this to establish the feasibility of the project. Moreover, sensitivity analysis was conducted, and a breakeven point of 211 tons of waste was obtained. In addition, the total benefit of recycling was valued and was given as R 486,008,582.85 (USD$ 35605572.16). From the overall analysis, it was observed that the IRR and Net Present Value were alike, about 677 potential jobs could be created on the project and the Net Present Value > 0. Based on the overall analysis, it was concluded that the project is viable.
This paper presents a review on sintered titanium nitride and titanium carbonitride-based cermets. TiN and TiCN based composites are remarkable class of cermets showing outstanding combination of ...hardness, high temperature strength and surface stability in tribology, corrosive or oxidative environments. These cermets play important roles in cutting tools and other high-temperature applications. Nonetheless, the cermets suffer some setback in toughness functionality required in cutting tools especially at high temperatures. Many researchers have worked on enhancing the hardness and toughness behaviours of TiCN using metallic binders to modify the toughness properties. The only achievement obtained was an improvement in high hardness with low toughness. This review is needed to evaluate the trends of achievement and development in the enhancement of optimum combination of hardness and toughness required in cutting tools applications. Additionally, it forecasts the essentiality of developing binderless phase TiCN with ultra-toughness that will significantly solve the deficiencies in high temperature application of TiCN as cutting tools.
Detailed prediction of the amounts of municipal solid waste (MSW) is very crucial for planning and management of MSW in a sustainable manner. Forecasting of MSW quantity is usually very challenging ...owing to unavailability of data in the low-income countries (LCs) and where data are available, they are often unreliable. The aim of this study is to forecast MSW generated in the City of Johannesburg (CoJ), South Africa with the projection period in continuing guesstimates by using machine learning approach. Two of machine learning algorithms namely: artificial neural network (ANN) and supported vector machine (SVM) were employed to forecast the quantity of MSW that would be generated in the CoJ. The forecast was based on historical data obtained from Statistics South Africa (STATS SA) and the projection was made up to 2050. The data pre-testing and incorporation structure was built in MATLAB simulation software to generate datasets having satisfactory information capacity and characteristic designed for modeling. From the result obtained, it was observed that machine learning algorithm is effective for the development of models for MSW forecasting. In the ANN models, the 10 neurons structure (ANN10) performed best with a determination coefficient (R2) of 99.9%, while in the SVM models, the linear model performed best with R2 of 98.6%. From the results obtained from the ANN10 model, the total amount of MSW generated per year in the City of Johannesburg is envisaged to get to 1.95 × 106 tonnes in 2050 with an average annual waste of 1.78 x 106 tonnes.
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•Forecasting MSW generation in long term duration in the City of Johannesburg.•Evaluation of Artificial neural network and Supported vector machine.•Data pre-testing and incorporation structure was built in MATLAB simulation software.
Composites of titanium nitride reinforced with graphite were synthesized using spark plasma sintering at 2000°C. The effects of graphite addition on the microstructure, relative density, and ...mechanical properties of TiN ceramics matrix were examined. The investigation was performed on TiN powder with varying graphite content (1–5wt.%) for 8h using an energy ball milling equipment. Results show that TiN without and with graphite (TiN+1wt.% graphite) sintered at 2000°C recorded sintered relative density of 96.7% and 97% respectively. Additionally, TiN with 3wt.% graphite had a relative density of 98%. However, the shrinkage of TiN+3wt.% graphite was observed to be the lowest compared to other composites at the same sintering conditions. Microstructural analysis indicates that the grain of titanium nitride in the composite was very fine and continuous. Subsequently, a bimodal particle sizes were observed when 5wt.% graphite was dispersed in TiN. The highest Vickers microhardness of 23.5GPa and fracture toughness of 6.5MPam1/2 were achieved with composites reinforced with 3wt.% graphite at milling period of 8h. The combination of TEM/EDS and HRTEM/FFT show a single pattern of diffraction and consistency in interplanar distance obtained from X-ray diffractometry of the milled sample. There is a clear coherence interface between the phases.
Abstract In this study, an artificial neural network model using function fitting neural networks was developed to describe the yield and quality of multi-walled carbon nanotubes deposited over ...NiMo/CaTiO 3 catalyst using waste polypropylene plastics as cheap hydrocarbon feedstock using a single-stage chemical vapour deposition technique. The experimental dataset was developed using a user-specific design with four numeric factors (input variable): synthesis temperature, furnace heating rate, residence time, and carrier gas (nitrogen) flow rate to control the performance (yield and quality) of produced carbon nanotubes. Levenberg–Marquardt algorithm was utilized in training, validating, and testing the experimental dataset. The predicted model gave a considerable correlation coefficient (R) value close to 1. The presented model would be of remarkable benefit to successfully describe and predict the performance of polypropylene-derived carbon nanotubes and show how the predictive variables could affect the response variables (quality and yield) of carbon nanotubes.
In the search of appropriate materials for producing machine tools, this study investigated the wear performance of Austempered grey cast iron (AGCI) and ductile iron (DI) done on a single way ...tribosystem. An alloy containing 1.2 kg of Fe-Si-Mg inoculated by 0.2%Ca-Si was introduced to the melt at 350 °C austempering temperatures after austenitizing at 900 °C for 180 min. However, the highest Coefficient of friction and resistance of materials to wear are independent of 2 N and 5 N applied loads, while 7 N, 8 N, and 10 N were strongly dependent on the load applied. The outcomes revealed that the Coefficient of friction generally rises as the applied load increases in AGCI and DI. Highest Coefficient of friction 0.8 was observed at 10 N in DI while 0.85 and 0.8 was observed at 10 N and 8 N for AGCI, due to strain-induced retained austenite transformation of the martensite and work hardening.
This study evaluates the pattern of energy usage at the twenty-eight residences of the University of Johannesburg during the 2016 academic year. The study investigates the trend of energy consumption ...based on the total energy usage per residence in terms of the number of students at each of the residences on a monthly and daily basis. The data employed in this study was collected over a period of eleven months which is the overall effective academic calendar. The results obtained showed a contrast between the total energy usage per residence and energy usage per student. Sophia town residence recorded the highest total annual energy usage of 1547937.92 kWh while Takalani residence recorded the least which was 101863.73 kWh of all the residences considered in this study. However, when energy consumption was measured as a function of number of students in each residence, Gauta residence recorded the highest monthly energy usage per student (5165.17 kWh), followed by YMCA (4643.84 kWh) while the least monthly energy usage of 581.09 kWh was recorded in Maqhawe residence. Similarly, results obtained from the study on daily energy usage per student in the last five months of the 2016 academic year showed YMCA residence (20.34 kWh) and Lebone (16.42 kWh) as the two residences with the highest daily energy usage per student respectively. However, the energy usage does not follow a regular pattern within the period under consideration.
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