Department of Geomatics and Surveying Publications
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Item Modeling COVID-19 infection in high-risk settings and low-risk settings(Elsevier, Science Direct, 2022-11-02) Ndlovu, Meshach; Mpofu, Mqhelewenkosi A.; Moyo, Rodwell G.In this research paper we present a mathematical model for COVID-19 in high-risk settings and low-risk settings which might be infection dynamics between hotspots and less risky communities. The main idea was to couple the SIR model with alternating risk levels from the two different settings high and low-risk settings. Therefore, building from this model we partition the infected class into two categories, the symptomatic and the asymptomatic. Using this approach we simulated COVID-19 dynamics in low and high-risk settings with auto-switching risk settings. Again, the model was analyzed using both analytic methods and numerical methods. The results of this study suggest that switching risk levels in different settings plays a pivotal role in COVID-19 progression dynamics. Hence, population reaction time to adhere to preventative measures and interventions ought to be implemented with flash speed targeting first the high-risk setting while containing the dynamics in low-risk settings.Item A numerical modelling approach for the optimisation of photovoltaic installations in the mitigation of thermal effects(Elsevier, Science Direct, 2022-06-22) Chiteka, K.; Madiye, L.; Chingosho, H.; Arora, R.; Enweremadu, C.C.Solar energy presents one of the best alternative sources of energy in the current bid to mitigate the negative impacts of global warming. The present study evaluated the influence of the installation configuration together with the meteorological parameters on the temperature characteristics of a solar photovoltaic array. Three dimensional simulation using Computational Fluid Dynamics was used in the numerical analysis of the temperature characteristics on solar PV arrays. The Shear Stress Transport k-ω model was employed to analyse the turbulent characteristics of the airstream near the photovoltaic array. A temperature prediction model was developed using Artificial Neural Networks and the model was found to be accurate with a coefficient of determination, R2 of 93.1 %. A Response Surface Methodology optimization model was developed to maximize energy generation while minimizing solar photovoltaic cell operating temperature. The models were able to reduce temperature and improve energy generated by a 3.9 %. The optimized tilt and azimuth angles were found to be 28.2o tilt and 13.2o, respectively, yielding an average cell temperature of 29.3 °C which gave a 3.9 % increase in energy and revenue generated.Item Modelling COVID-19 infection with seasonality in Zimbabwe(Elsevier, Science Direct, 2022-05-25) Ndlovu, Meshach; Moyo, Rodwell; Mpofu, MqhelewenkosiThis paper presents evidence and the existence of seasonality in current existing COVID-19 datasets for three different countries namely Zimbabwe, South Africa, and Botswana. Therefore, we modified the SVIR model through factoring in the seasonality effect by incorporating moving averages and signal processing techniques to the disease transmission rate. The simulation results strongly established the existence of seasonality in COVID-19 dynamics with a correlation of 0.746 between models with seasonality effect at 0.001 significance level. Finally, the model was used to predict the magnitude and occurrence of the fourth wave.