Research Publications (Engineering and Built Environment)
Permanent URI for this collectionhttp://ir-dev.dut.ac.za/handle/10321/215
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Item Gender and gender mainstreaming In engineering education in Africa(Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP, 2020) Fomunyam, Kehdinga George; Matola, Noluthando; Moyo, SibusisoIn Africa, a lot of debates on the issues of gender gap and gender inequality has raised concerns in engineering education (EE) and engineering workforce. Thus, gender inequality and equity are significant in realizing Sustainable Development Goals (SDGs), and in recent years much has been done to address gender gaps, yet women are still excluded, underrepresented, segregated and relegated inengineering profession and academia. With much sensitization on gender equality, Africa is still far from addressing gender gaps in EE; hence the crux of this paper. This paper was guided by Liberal Feminism theory, focusing on women’s freedom as an autonomy to be free from coercive interference, due to‘gender system’ or patriarchal nature of inherited traditions and institutions. This paper takes a broad look at the concepts of gender and gender mainstreaming in EE in Africa. Specifically, it explores gender and inequality in EE and how gender mainstreaming canbe enacted to address gender gaps in EE, as well as its implications in Africa. Thus, to address these gaps, recommendations such as developing gendersensitive curriculum for EE, adopting policies in facilitating women’s access to training and employment opportunities as well as creating gender-sensitive career counselling were advocatedItem Comparative analysis of different computational intelligence techniques for maximum power point tracking of PV systems(University of Oradea, 2022-10-01) Moyo, Ranganai Tawanda; Tabakov, Pavel Y.; Moyo, SibusisoThe performance of a photovoltaic (PV) module can be improved by employing maximum power point tracking (MPPT) controllers. MPPT controllers are algorithms that are included in PV battery charge controllers or inverters to extract the maximum available power from PV modules for any given temperature and irradiance. Several studies report that the use of PV modules without MPPT controllers results in power losses, which ultimately results in the need to install more solar panels for the same power requirement. Numerous techniques of varying complexities have been proposed in the literature to solve the MPPT objective function. This paper presents a comparative analysis of three computational intelligence (CI) based MPPT techniques namely, the fuzzy logic (FL) based controller, artificial neural networks (ANN) based controller, adaptive neuro-fuzzy inference system (ANFIS) based controller and one conventional technique, the perturbation and observation (P&O) controller. These MPPT controllers are designed, simulated and analysed in the MATLAB/Simulink environment. The performance of the studied MPPT techniques is evaluated under steady-state weather conditions, rapidly changing weather conditions and varying load conditions. CI-based MPPT controllers are found to be more efficient than the P&O controller. Moreover, the ANFIS-based MPPT controller shows an outstanding MPPT performance for all the scenarios studied.Item Design and modeling of the ANFIS-based MPPT controller for a solar photovoltaic system(ASME International, 2021-08) Moyo, Ranganai T.; Tabakov, Pavel Y.; Moyo, SibusisoAbstract Maximum power point tracking (MPPT) controllers play an important role in improving the efficiency of solar photovoltaic (SPV) modules. These controllers achieve maximum power transfer from PV modules through impedance matching between the PV modules and the load connected. Several MPPT techniques have been proposed for searching the optimal matching between the PV module and load resistance. These techniques vary in complexity, tracking speed, cost, accuracy, sensor, and hardware requirements. This paper presents the design and modeling of the adaptive neuro-fuzzy inference system (ANFIS)-based MPPT controller. The design consists of a PV module, ANFIS reference model, DC–DC boost converter, and the fuzzy logic (FL) power controller for generating the control signal for the converter. The performance of the proposed ANFIS-based MPPT controller is evaluated through simulations in the matlab/simulink environment. The simulation results demonstrated the effectiveness of the proposed technique since the controller can extract the maximum available power for both steady-state and varying weather conditions. Moreover, a comparative study between the proposed ANFIS-based MPPT controller and the commonly used, perturbation and observation (P&O) MPPT technique is presented. The simulation results reveal that the proposed ANFIS-based MPPT controller is more efficient than the P&O method since it shows a better dynamic response with few oscillations about the maximum power point (MPP). In addition, the proposed FL power controller for generating the duty cycle of the DC–DC boost converter also gave satisfying results for MPPT.Item Data pre-processing for process optimization at a drinking water treatment plant in Ugu District Municipality, South Africa(Business Perspectives, 2015) Magombo, James; Dzwairo, Bloodless; Moyo, Sibusiso; Dewa, MendonWhen testing and recording water quality data from treatment plants, errors arise. The errors are in the form of re-cordings left blank (missing values), obvious errors in writing or typing, or they can be as a result of values being very small to detect and are therefore censored. The censored values are known to be below the limit of detection (LOD). In statistical analysis, the blank cells can be filled with a certain value. Censored values are often corrected by substituting with a constant value throughout. This value will be a fraction of the limit of detection and most commonly used frac-tions are, half the limit of detection, the limit of detection divided by the square root of 2, or multiplying the limit of detection by 0.75. The direct substitution method for handling missing and values below the limit of detection results in a uniform distribution for values below the limit of detection, and a true distribution for those above. As a result, treat-ment of the values below the limit of detection is dependent upon their percentage in the sample size. An alternative method used will mimic the characteristic of the distribution pattern of the values above the limit of detection to esti-mate the values below it. This can be done with an extrapolation technique or maximum likelihood estimation. In this study, data from the Umzinto Water Treatment Plant was used to develop a data pre-processing program using Visual Basics for Applications (VBA) and Microsoft Excel 2013. The procedure involved 4 stages: data preparation, data pre-processing for blanks and non-detects, data pre-processing for the censored values and finally the identifica-tion of the outliers. The developed program was then used to pre-process raw water quality data, which resulted in satisfactory process time and data conversion. The methodology used can be borrowed for the pre-processing of data driven environmental models and hence it has a great influence on sustainability of water treatment plants.Item A comparative analysis of evolutionary algorithms in the design of laminated composite structures(De Gruyter, 2015) Tabakov, Pavel Y.; Moyo, SibusisoAbstract: The increased use of composite materials and structures in many engineering applications led to the need for a more accurate analysis and design optimi-zation. While methods of stress-strain analysis devel-oped faster, optimization techniques have been lagging behind. As a result, many designed structures do not ful-fill their full potential. The present study demonstrates the major achievements in recent years in an application of evolutionary algorithms to the design optimization of fiber-reinforced laminated composite structures. Such structures are of much interest due to high structural design sensitivity to fiber orientations as well as complex multidimensional discrete optimization problems. Using an anisotropic multilayered cylindrical pressure vessel and an exact elasticity solution as an example, we show how the optimum, or near–optimum, solution can be found in a more efficient way.