Faculty of Engineering and Built Environment

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The academic benefit of experiential learning for Civil Engineering students on the Pietermaritzburg campus of the Durban University of Technology
(SASEE, 2013-06) McKune, Tom
Acetic acid adsorption onto activated carbon derived from pods of Acacia nilotica var astringens (Sunt tree) by chemical activation with ZnCl2
(IISTE, 2015) Elhussien, Mutasim H.; Isa, Yusuf Makarﬁ
The purpose of this study is to prepare and investigate the adsorption behavior of acetic acid onto two samples of activated carbon prepared from Acacia nilotica var astringens, Sunt tree,( SUNT-C1 and SUNT-C2). Applicability Langmuir, Freundlich, Temkin and Dubinin-Radushkevitch models of adsorptions isotherm have been tested, while acetic acid initial concentration varied between (0.010 – 0.300) mol/dm3. A comparative study of adsorption capacities of these samples was performed. The obtained data were compared and fitted well with the four models; there exist a correlation between physico- chemical properties of the activated carbons and the sorption processes. The maximum monolayer coverage (Qo) from Langmuir isotherm model was determined to be 1.016mg/g. Also from Freundlich Isotherm model, the sorption intensity (n) which indicates favourable sorption and the correlation value are 1.11 and 1.09 respectively.
An adaptive neuro-fuzzy inference scheme for defect detection and classification of solar Pv cells
(Academy Publishing Center, 2024-09-12) Moyo, Ranganai Tawanda; Dewa, Mendon; Romero, Héctor Felipe Mateo; Gómez, Victor Alonso; Aragonés, Jose Ignacio Morales; Hernández-Callejo, Luis
This research paper presents an innovative approach for defect detection and classification of solar photovoltaic (PV) cells using the adaptive neuro-fuzzy inference system (ANFIS) technique. As solar energy continues to be a vital component of the global renewable energy mix, ensuring the reliability and efficiency of PV systems is paramount. Detecting and classifying defects in PV cells are crucial steps toward ensuring optimal performance and longevity of solar panels. Traditional defect detection and classification methods often face challenges in providing precise and adaptable solutions to this complex problem. In this study the researchers pose an ANFIS-based scheme that combines the strengths of neural networks and fuzzy logic to accurately identify and classify various types of defects in solar PV cells. The adaptive learning mechanism of ANFIS enables the model to continuously adapt to changes in operating conditions ensuring robust and reliable defect detection capabilities. The ANFIS model was developed and implemented using MATLAB and a high predicting accuracy was achieved.
Advanced distributed cooperative secondary control of Islanded DC Microgrids
(MDPI AG, 2022-05-28) Aluko, Anuoluwapo; Buraimoh, Elutunji; Oni, Oluwafemi Emmanuel; Davidson, Innocent Ewean
In an islanded DC microgrid with multiple distributed generators (DGs), the droop control is employed to realize proportional current sharing among the DGs in the microgrid. The action of the droop control causes a deviation in the DC bus voltage which is exacerbated by the line impedance between the DG and the DC bus. In this paper, an advanced distributed secondary control scheme is proposed to simultaneously achieve accurate voltage regulation and cooperative current sharing in the islanded DC microgrid system. The proposed distributed secondary controller is introduced in the cyber layer of the system, and each controller shares information with neighbouring controllers via a communication network. The distributed technique maintains the reliability of the overall system if some part of the communication link fails. The proposed controller uses the type-II fuzzy logic scheme to adaptively select the secondary control parameters for an improved response of the controller. The sufficient conditions to guarantee the stability of the proposed controller are derived using the Lyapunov method. Comprehensive tests under different operating scenarios are conducted to demonstrate the robustness of the proposed control scheme.
Advances in sintering of titanium aluminide : a review
(Springer Science and Business Media LLC, 2022) Mphahlele, Mahlatse R.; Olubambi, Peter Apata; Olevsky, Eugene A.
Analysis of current Pulses in HeLa-Cell Permeabilization due to high voltage DC corona discharge
(IEEE, 2016-09) Chetty, Nevendra K.; Chonco, Louis; Ijumba, Nelson M.; Chetty, Leon; Govender, Thavendran; Parboosing, Raveen; Davidson, Innocent Ewaen
Corona discharges are commonly utilized for numerous practical applications, including bio-technological ones. The corona induced transfer of normally impermeant molecules into the interior of biological cells has recently been successfully demonstrated. The exact nature of the interaction of the corona discharge with a cell membrane is still unknown, how-ever, previous studies have suggested that it is either the electric ﬁelds produced by ions or the chemical interaction of the reactive species that result in the disruption of the cell membrane. This disruption of the cell membrane allows molecules to permeate into the cell. Corona discharge current constitutes a series of pulses, and it is during these pulses that the ions and reactive species are produced. It stands to reason, therefore, that the nature of these corona pulses would have an inﬂuence on the level of cell permeabilization and cell destruction. In this investigation, an analysis of the width, rise-time, characteristic frequencies, magnitude, and repetition rate of the nanosecond pulses was carried out in order to establish the relationship between these factors and the levels of cell membrane permeabilization and cell destruction. Results obtained are presented and discussed.
Analysis of electric-rubber tyred gantries for a more green Durban Container Terminal
(International Organization Of Scientific Research (IOSR), 2015-06) Naicker, Rowen; Allopi, Dhiren
The Durban Container Terminal (DCT) is currently the biggest and busiest container terminal in Africa and handles about 2.7-million TEUs a year. DCT handles approx. 70% of South Africa’s containers and generates 60% of South Africa’s revenue (Port of Durban, 2014). The work-horse of the container handling industry is the Rubber Tyred Gantry (RTG) crane. For over 50 years, these heavy duty cranes have been a staple at ports worldwide. Typically powered by diesel engines, these cranes require constant maintenance and fuel management to remain operational. In addition to costs, ports have begun to feel the pressure to become more “Green” by local authorities and governments.Pier 1, at DCT is currently utilizingRTGs. High energy consumption and high pollution result from RTGs operating around the clock. This entails a high cost burden for terminal operators and causes serious environmental pollution.An investigation into solutions to lessen operating costs, strengthen business competitiveness, and alleviate environmental pollution is presented in this paper. The results were analyzed and conclusions, as well as recommendations were made.
Analysis of temperature and rainfall trends in Vaal-Harts irrigation scheme, South Africa
(AJER, 2014) Adeyemo, Josiah; Otieno, Fredrick Alfred O.; Ojo, Olumuyiwa I.
Abstract: - Agriculture is crucially dependent on the timely availability of adequate amount of water and a conducive climate. Temperature and rainfall patterns impact the availability of water for agricultural uses. Therefore, temperature and rainfall are twin important environmental factors in agricultural activities such as tillage, planting, irrigation and mechanization. The characteristics of the Vaal-Harts temperature data for year 1996 to 2010 and rainfall data for year 1983 to 2010 were examined in this study using statistical techniques. Basic statistical properties of the data were determined using the mean, variance, coefficient of variation and Pearson’s correlation coefficient. Temperature and rainfall observations with the average of about 17.44 were used. The minimum and maximum temperatures recorded were 9.720C and 23.520C. The Coefficient of variation (CV) was found to be about 29.59. Variance is a measure of how far a set of numbers is spread out; and the variance of this set of observations is 26.625. The average yearly temperature increases insignificantly by a constant of about 0.117 (p = 0.163; 95% CI: -0.054 – 0.288), while rainfall shows decreasing trend annually which means that the dry season will be drier. The involvement of non-zero values in the serial correlation indicated the significance of the deterministic component in the data. The results of this analysis enhance our understanding of the characteristics of air temperature and rainfall in the study area for effective planning of farming operations.
Analysis of voltage rise phenomena in electrical power network with high concentration of renewable distributed generations
(Springer Science and Business Media LLC, 2022-12) Akinyemi, Ayodeji Stephen; Musasa, Kabeya; Davidson, Innocent E.
The increasing penetration levels of renewable distributed generation (RDG) into a power system have proven to bring both positive and negative impacts. The occurrence of under voltage at the far end of a conventional electrical distribution network (DN) may not raise concern anymore with RDGs integration into a power system. However, a penetration of RDGs into power system may cause problems such as voltage rise or over-voltage and reverse power flows at the Point of Common Coupling (PCC) between RDG and DN. This research paper presents the impact of voltage rise effect and reverse power flow constraint in power system with high concentration of RDG. The analysis is conducted on a sample DN, i.e., IEEE 13-bus test system, with RDG penetration by considering the most critical scenario such as low power demand in DN and a peak power injection by RDG. For studying the impact of voltage rise and reverse power flow, a mathematical model of a DN integrating RDG is developed. Furthermore, a controller incorporating an advance control-algorithm is proposed to be installed at PCC between DN and RDG to regulate the voltage rise effects and to mitigate the reverse power flow when operating at a worst critical scenario of minimum load and maximum generation from RDG. The proposed control strategy also mitigates the voltage–current harmonic distortions, improves the power factor, and maintain the voltage stability at PCC. The simulations are carried out using MATLAB/Simulink software. Finally, recommendations are provided for the power producers to counteract the effects of voltage rise at PCC. The study has demonstrated that, voltage at PCC can be sustained with a high concentration of RDG during a worst-case scenario without a reverse power flow and voltage rise beyond grid code limits.
ANN’s vs. SVM’s for image classification
(International ASET, 2012-08) Moorgas, Kevin Emanuel; Pillay, Nelendran; Governder, Poobalan
In this paper the dynamic performance of the artificial neural network is compared to the performance of a statistical method such as the support vector machine. This comparison is made with respect to an image classification application where the performance is compared with regards to generalization and robustness. Image vectors are compressed in order to reduce the dimensionality and the salient feature vectors are extracted with the principle component algorithm. The artificial neural network and the support vector machine are trained to classify images with feature vectors. A comparative analysis is made between the artificial neural network and the support vector machine with respect to robustness and generalization.
The applicability of nanofiltration for the treatment and reuse of textile reactive dye effluent
(AJOL, 2015) Chollom, Martha Noro; Rathilal, Sudesh; Pillay, Visvanathan Lingamurti; Alfa, Dorcas
The main aim of the study was to test the feasibility of using nanofiltration (NF) processes for the treatment of reactive dye-bath effluents from the textile industry, in order to recover the water and chemicals (salts) for reuse purposes. The study of the reusability of nanofiltered water for dyeing has been given little or no attention. About 30% of reactive dyes remain unfixed on fibres; the unfixed dyes are responsible for the colouration in effluents. Membrane processes were employed to treat reactive dye-bath effluents to recover the salts and water. Investigations were conducted firstly with ultrafiltration (UF) used as a pre-treatment for NF. Secondly, evaluations were performed for 2 types of NF membranes (SR90 and NF90), in terms of quality of permeate produced and fluxes achieved for 2 different samples of effluent. The effect of cleaning on membrane performance was assessed. A reusability test was carried out on both permeate samples for dyeing light and dark shade recipes. The use of UF as pre-treatment to NF resulted in rejection of colloidal substances > 90% and a 15% flux improvement. Permeate from NF90 had a conductivity of 76 µS/cm and total organic carbon (TOC) of 20 mg/ℓ, as compared to SR90 which had a conductivity of 8.3 mS/cm and a TOC of 58 mg/ℓ. Light shade from NF90 gave satisfactory results on dyeing, with no colour difference. However a variation in colour was noticed when the medium sample was used to dye the light shade. Both NF permeates gave satisfactory results when used to dye the dark shades. Permeate from NF90 was within the accepted range for reuse, while permeate from SR90 had a higher salt recovery. Chemical cleaning resulted in 80% flux recovery. From the reusability test it was concluded that permeate from NF90 met the reuse criteria for feed water to the dye bath.
Application of mine tailings sand as construction material : a review
(EDP Sciences, 2022) Ikotun, Jacob; Adeyeye, Rhoda; Otieno, Mike
Tailings are found during the exploration and processing of mineral ores. They contain a mixture of grounded rocks, processed effluent, and some trace elements that have the potential to damage the environment. Recent urbanisation has led to a large stockpile of tailings in many mining environment constituting health hazard. It becomes very important to develop disposal techniques that will reduce the huge mountain of tailings in mining environment. One of such method is the application of tailings in sustainable concrete production. It is shown that physical and chemical characteristics of tailings are comparable to crusher sand used in engineering construction and therefore, tailings can be used to partially replace sand in bituminous and concrete mixtures. In this review, specific interest has been given to iron, copper, and gold tailings, this is due to their dominance in mining areas of Kwa-Zulu Natal province of South Africa.
Application of neural network in chemical and non-chemical engineering problems
(South African Institution of Chemical Engineers, 2015) Chetty, Maggie; Carsky, M.; Kormuth, E.
Use of a neural network approach to the solution of complex tasks is demonstrated on first, the identification of a food chemical specification (“Chemical Engineering case”) and second, the prediction of survival and prognosis for leukaemia patients (“Non-Chemical Engineering case”). In the first case product colour was identified as an important quality feature, which significantly affects marketing of food grade antioxidants used for preservation of edible oils. The product quality is specified in terms of the “Lovibond colour index”. Production of phenolic antioxidant in a well-established operation exhibited for an extended period of time a variation of the product colour. Due to the complexity of the technological process it is impossible to pinpoint a simple reason for variations. The product is synthesised in a batch reactor, the crude product is then recovered from post-reaction batch via crystallisation and refined in a complex purification process to get the final product, which meets specification. It is unclear, whether the undesirable colour is formed during the synthesis itself or results from underperformance of the purification process. Data from the manufacturing process were collected over 140 batches, where the impurity profile of crude product was recorded along with some other purification parameters. Impurity profile included an occurrence of 32 different compounds, some of them occurring on a random basis. The neural network model predicts the final product quality on the basis of a crude product impurity profile. Thus the process management decision to premeditate the product can be made well in advance during the process. Should the prediction show that the final product would not meet the required specification, corrective measures can be implemented well in advance to rescue the final product. In the second case the neural network model attempts to predict survival rate of leukaemia patients over two and three year periods based on 38 medical factors of patients and treatment procedures chosen, Which make it possible to apply the right treatment at an early stage.
Applications of artificial intelligence to photovoltaic systems : a review
(MDPI AG, 2022) Mateo Romero, Héctor Felipe Mateo; González Rebollo, Miguel Ángel González; Cardeñoso-Payo, Valentín; Alonso Gómez, Victor Alonso; Redondo Plaza, Alberto Redondo; Moyo, Ranganai Tawanda; Hernández-Callejo, Luis
This article analyzes the relationship between artificial intelligence (AI) and photovoltaic (PV) systems. Solar energy is one of the most important renewable energies, and the investment of businesses and governments is increasing every year. AI is used to solve the most important problems found in PV systems, such as the tracking of the Max Power Point of the PV modules, the forecasting of the energy produced by the PV system, the estimation of the parameters of the equivalent model of PV modules or the detection of faults found in PV modules or cells. AI techniques perform better than classical approaches, even though they have some limitations such as the amount of data and the high computation times needed for performing the training . Research is still being conducted in order to solve these problems and find techniques with better performance. This article analyzes the most relevant scientific works that use artificial intelligence to deal with the key PV problems by searching terms related with artificial intelligence and photovoltaic systems in the most important academic research databases. The number of publications shows that this field is of great interest to researchers. The findings also show that these kinds of algorithms really have helped to solve these issues or to improve the previous solutions in terms of efficiency or accuracy.
An appropriate Bus Rapid Transit System
(IJST Publications, 2014-04) Adewumi, Emmanuel Olusegun; Allopi, Dhiren
Bus Rapid Transit (BRT) has been adopted as an improvement on regular bus services through the combination of features like infrastructure changes that resulted in better operation speeds and service reliability. In this regards, it does pose a problem in selecting a BRT that is most suitable for a particular area/region. Hence, this study suggests an appropriate BRT system during in-depth literature review. To be able to select the appropriate vehicle option for a BRT system for a particular area/corridor, the transport demand, coverage/distance to be covered and length of public transport delay due to general traffic condition must be put into proper consideration. In terms of cost implication, median BRT system and kerbside BRT system should be selected over segregated BRT system.
Architecture of optical communications and systems
(ABE-IPS Books Online Journal, 2015) Ilcev, Stojce Dimov
Assessing the impact of undergraduate research on graduate attributes development : a case study of DUT Civil Engineering Students
(Durban University of Technology, 2022) Ngubane, Zesizwe; Hay, Shanley; Adedeji, Jacob Adedayo
Engineering graduates are expected to demonstrate competence after their engineering programmes in the form of graduate attributes (GAs) prescribed by the Engineering Council of South Africa (ECSA). It has, however, been challenging to develop and assess these attributes, especially using conventional assessment or examination methods, just as on the global scale. Nevertheless, studies have demonstrated that undergraduate research enables students to develop independent critical skills, as they do in graduate studies, by identifying a problem that needs to be solved. Undergraduate research has not been widely explored as a tool in developing and accessing GAs in engineering students. This study examined the impact of undergraduate research in engineering student ECSA GAs development and assessment using a case study of civil engineering diploma students. Therefore, using purposeful quantitative sampling methods, first-year and second-year diploma students were interviewed on their experience with newly introduced undergraduate research. Observations of the students' responses indicated that students' understanding, and views of GAs do improve from the first year to the second year due to continuous exposure to research. A conceptual model for assessing and developing GAs among engineering students is proposed in this study. This conceptual framework can assist in the further development of strategies in the implementation of undergraduate research at universities of technology.
Assessing the safety of training firefighters with the minimum requirements for firefighter garments
(Springer, 2021-03-23) Clark, Thomas B. B; Walker, Mark; Mendham, Frank
Every year, high numbers of firefighters are injured at fire incidents. A primary cause of moderate to severe injury can be linked to the protective garments worn by firefighters and understanding the limits of these protective garments is crucial for their safety. It would be substantially advantageous to firefighter safety if their available safe escape time is included in building design. To do this, the heat protective performance of firefighter garments needs to be translated into a tenable time. In this study, the minimum Thermal Protective Performance (TPP) rating of firefighter garments was investigated and found to compare well to known firefighter environments. This TPP rating was then used to further process the heat flux results from a CFD based fire model to determine an available safe escape time for firefighters. The probability of firefighters being injured was required in this study. It was used to assess the accuracy of the fire model in estimating the critical heat flux required to prevent a safe available escape time.
An assessment of environmental RF noise due to IoT deployment
(MDPI AG, 2023-09) Ingala, Dominique G.K.; Pillay, Nelendran; Pillay, Aritha
The advent of the Internet of Things (IoT) has contributed to an increase in the production volume of RF-featured equipment. According to statistics from the literature, the IoT industry will soon deploy billions of products. While the concept behind these applications seems exciting, this paper sought to assess the effects the radio emissions produced by IoT products would have on the ambient radio noise levels within the unlicensed frequency bands of 433 MHz, 868 MHz, and 2.4 GHz. The study extended to three environments: industrial, urban, and suburban. This study developed an IoT noise generator (ING) device to emulate RF noise signals in the desired IoT radio transmission band. The paper presents a simplified radio noise surveying system (RNSS) for data collection of ambient radio noise from five South African candidate sites. The statistical and empirical analysis agree that the level of ambient radio noise was directly proportional to the rate of IoT radio activities. The slopes of the regression lines demonstrate that 80% of the analyzed data developed augmenting trends. Approximately 20% of the data show declining trends.
Automation verses National Development Plan
(IJESMR, 2015-09) Naicker, Rowen; Allopi, Dhiren
The Durban Container Terminal (DCT) is currently the biggest and busiest container terminal in Africa and handles about 2.7-million TEUs a year. DCT handles approximately 70% of South Africa’s containers and generates 60% of South Africa’s revenue (Port of Durban, 2014). The industry move to automate is being driven primarily, though, by the need to efficiently handle big ships. This requires a step up in innovation. Increasing the automation level of a terminal with products that automate a single part of the operation or the whole process is recognised as the next step towards improving performance at today’s container terminals. The benefits of automation include lower operational costs as well as improved terminal productivity, capacity, safety and security. Besides the actual automated system, there is also extensive change management within the entire organisation of the terminal, as operating an automated terminal requires a thorough change of business processes as well as different skill sets for the people operating the terminal. The biggest hurdle though is embedding this concept in South African ports considering the fact that South Africa’s National Development Plan (NDP) stipulates that government’s desire to increase employment from 13 million in 2010 to 24 million in 2030 (The National Planning Commission 2012: 34).