Research Articles (Mechanical and Aeronautical Engineering)

Permanent URI for this collectionhttp://hdl.handle.net/2263/1705

Browse

Now showing 1 - 20 of 787

Using of artificial neural networks (ANNs) to predict the rheological behavior of magnesium oxide-water nanofluid in a different volume fraction of nanoparticles, temperatures, and shear rates
Li, Yicheng; Kalbasi, Rasool; Karimipour, Arash; Sharifpur, Mohsen; Meyer, Josua P. (Wiley, 2026-04)
Laboratory studies are usually time-consuming and costly; hence, soft computing methodology can be an attractive alternative for predicting results. In this study, the viscosity of MgO-water nanofluid in a different volume fraction of nanoparticles, temperatures, and shear rates has been predicted by artificial neural networks (ANNs) and surface methods. In the ANN method, an algorithm is proposed to select the best neuron number for the hidden layer. In the fitting method, a surface is proposed for each volume fraction of nanoparticles, and finally, the results of the ANN and surface fitting method have been compared. It can be observed that increasing the volume fraction from 0.07% to 1.25% at temperatures of 25°C, 30°C, 40°C, 50°C, and 60°C resulted in about two-fold increase in viscosity. Also, the best network has 24 neurons in the hidden layer. It can be seen that for a network with 24 neurons in the hidden layer has the best overall correlation, and this coefficient is 0.999035. The mean absolute value of errors in the ANN and fitting method are 0.0118 and 0.0206, respectively.
Towards scientific machine learning for granular material simulations : challenges and opportunities
Fransen, Marc; Furst, Andreas; Tunuguntla, Deepak; Wilke, Daniel Nicolas; Alkin, Benedikt; Barreto, Daniel; Brandstetter, Johannes; Cabrera, Miguel Angel; Fan, Xinyan; Guo, Mengwu; Kieskamp, Bram; Kumar, Krishna; Morrissey, John; Nuttall, Jonathan; Ooi, Jin; Orozco, Luisa; Papanicolopulos, Stefanos-Aldo; Qu, Tongming; Schott, Dingena; Shuku, Takayuki; Sun, Waiching; Weinhart, Thomas; Ye, Dongwei; Cheng, Hongyang (Springer, 2026-01)
Micro-scale mechanisms, such as inter-particle and particle-fluid interactions, govern the behaviour of granular systems. While particle-scale simulations provide detailed insights into these interactions, their computational cost is often prohibitive. At a recent Lorentz Center Workshop on “Machine Learning for Discrete Granular Media”, researchers explored how machine learning approaches can aid the development of constitutive laws and efficient data-driven surrogates for granular materials while also addressing uncertainty quantification. Attended by researchers from both the granular materials (GM) and machine learning (ML) communities, the workshop brought the ML community up to date with GM challenges. This position paper emerged from the workshop discussions. In this position paper, we define granular materials and identify seven key challenges that characterise their distinctive behaviour across various scales and regimes–ranging from gas-like to fluid-like and solid-like. Addressing these challenges is essential for developing robust and efficient models for the digital twinning of granular systems in various industrial applications. To showcase the potential of ML to the GM community, we present classical and emerging machine/deep learning techniques that have been, or could be, applied to granular materials. We reviewed sequence-based learning models for path-dependent constitutive behaviour, followed by encoder-decoder type models for representing high-dimensional data in reduced spaces. We then explore graph neural networks and recent advances in neural operator learning. The latter captures the emerging field evolution of interacting particles via efficient latent space representation. Lastly, we discuss model-order reduction and probabilistic learning techniques for high-dimensional parameterised systems, both of which are crucial for quantifying and incorporating uncertainties arising from physics-based and data-driven models. We present a typical workflow aimed at unifying data structures and modelling pipelines and guiding readers through the selection, training, and deployment of ML surrogates for granular material simulations. Finally, we illustrate the workflow’s practical use with two representative examples, focusing on granular materials in solid-like and fluid-like regimes.
Intra-island variation in wind patterns on sub-Antarctic Marion Island
Schoombie, Janine; Craig, K.J. (Kenneth); Goddard, Kyle Andrew; Hedding, D.W. (David William); Nel, W.; Le Roux, Peter Christiaan (University of Pretoria, 2025-10)
Sub-Antarctic Marion Island provides a critical habitat for pelagic species, yet its terrestrial ecosystem faces increasing threats from climate change. Despite being situated in one of the windiest regions globally, the impact of changing wind patterns at the intra-island scale remains poorly understood. Existing datasets lack the spatial resolution necessary to capture fine-scale wind dynamics across the island. This study aimed to address this gap by presenting high-resolution wind speed and direction data to investigate the effects of wind on terrestrial systems. We present two complementary datasets: (1) wind measurements collected from 17 stations distributed across the island between May 2018 and March 2021, and (2) computational fluid dynamics (CFD) simulations providing wind vectors and associated properties at a 30 × 30 m resolution for heights up to 200 m above ground level. The data reveal significant differences in wind speed and direction across different geographical sectors of Marion Island. Notably, anemometers situated in the south recorded more frequent gale-force winds, while the western stations experienced calmer conditions. By using the observed wind direction frequencies, a weighted average vector plot was generated from the CFD simulations, providing an island-scale representation of spatial wind patterns across the island. These datasets offer valuable insights into variations in wind patterns, including upstream and downstream effects, and serve as a crucial resource for studying wind-driven processes affecting the landscape and ecosystem, such as seed dispersal.
Development of a predictive, risk-based model to assess the effects of maintenance decisions on vertical mine shaft structures
Wannenburg, Johann; Ngcobo, Glory Nomvula; Heyns, P.S. (Philippus Stephanus) (Elsevier, 2026-05)
PURPOSE : The study addresses the challenge of effective long-term maintenance of the structures of vertical mine shafts. These structures face significant degradation over time due to corrosion, the impact of falling objects, and exposure to harsh environments with high humidity, chemical contamination, and poor ventilation. Current maintenance practices often prioritise short-term needs, neglecting the long-term consequences for structural integrity and operational sustainability. To bridge this gap, the research introduces a novel predictive risk-based maintenance decision-making model. DESIGN/METHODOLOGY/APPROACH : The model incorporates finite element analysis and Monte Carlo simulations to evaluate the failure modes caused by corrosion, fatigue and falling objects while accounting for uncertainties in degradation rates and impact probabilities. The analysis calculates the energy of falling objects and estimates corrosion rates based on environmental conditions, enabling accurate predictions of the remaining useful life (RUL) of critical steel components. This is combined with an Integrated Structural Inspection and Maintenance Management (iSIMM) system, which combines structural inspection data with Computerised Maintenance Management Systems (CMMS). ORIGINALITY/VALUE : This model enables informed decision-making, enhancing safety, reliability, and cost-efficiency in mining operations. The research’s novelty lies in the integration of predictive and risk-based maintenance strategies, offering new insights into managing mine shaft structural integrity whilst integrating quantitative FEA-derived damage models (for impact) with stochastic, inspection-driven lifecycle simulation as a key methodological that enables the transition from qualitative inspection to predictive, risk-informed planning. FINDINGS : The model is used in a case study of a South African gold mine and demonstrates the practical application, showcasing its ability to optimise maintenance planning, reduce life cycle costs, and extend the lifespan of mine shafts, and to quantify the cost-risk trade-off between different multi-year maintenance strategies, a decision-support feature often missing in practice.
Multi-dish configurations for single-shaft and parallel-flow solar-dish Brayton cycles
Cockcroft, C.C. Le Roux; Le Roux, Willem Gabriel (Elsevier, 2025-12)
Concentrating solar power combined with parallel-flow Brayton cycles can form a viable solution to generating cleaner and more sustainable energy. Parallel-flow Brayton cycles are not influenced as greatly as traditional single-shaft cycles when solar and/or recuperation components are added to the cycle. To further improve the thermal efficiency of parallel-flow cycles, the solar heat input to the cycles can be increased through introducing a second solar receiver in the setup (a multi-dish setup). This analytical study addresses the viability of incorporating multi-dish configurations in parallel-flow and single-shaft Brayton cycles. The study is based on using off-the-shelf automotive turbochargers to develop a solarised micro gas turbine for power generation. It is determined that a multi-dish cycle setup adds performance improvement to the thermal efficiency results in both single-shaft and parallel-flow recuperated solar cycles. When the best-performing multi-dish recuperated low-temperature turbine (LTT) cycle is considered, the thermal efficiency is 69 % greater than in the best-performing single-dish recuperated LTT cycle. The multi-dish recuperated single-shaft cycle, however, obtains 3.2 % less thermal efficiency than the single-dish recuperated single-shaft cycle. The multi-dish single-shaft power output is greatly restricted by high solar receiver surface temperatures, which is not the case in the multi-dish recuperated LTT cycle. Therefore, more solar heat can be captured in the parallel-flow multi-dish LTT cycle.
CFD modelling of convective falling films for enhanced algae cultivation : fluid mechanics influence of mass transfer
Lancaster, Gerald; Bock, Bradley D.; Craig, K.J. (Kenneth) (EDP Sciences, 2026-01-14)
Falling film photobioreactors are able to increase the mass transfer rates per volume of liquid through the gas-liquid interface compared to other photobioreactor types. At low Reynolds numbers the flow mass transfer is still diffusion limited. This work aims to resolve and improve the convective mixing within thin falling films numerically to optimize the rates of CO2 absorption into a thin falling water film. Flat plate models are compared and it is found that slower films with a Reynolds number of 28 outperform faster flowing films by up to 2.5 times.
Enhancing the hydrothermal and economic efficiency of parabolic solar collectors with innovative semi-corrugated absorber tubes, shell form cone turbulators, and nanofluid
Samad, Sarminah; Saeidlou, Salman; Khan, M. Nadeem; Alamry, Ali; Al-Harbi, Laila M.; Sharifpur, Mohsen; Ghoushchi, S.P. (Elsevier, 2025-11)
This study proposes a performance-enhancing design for parabolic trough solar collectors by integrating a novel semi-corrugated absorber tube with an innovative shell-form cone turbulator, operating with CuO–water nanofluid. Numerical simulations were conducted across a Reynolds number range of 4500–10,930 to evaluate the effects of corrugation radius (0.5–1.5 mm), nanofluid volume fraction (1–3 %), and turbulator geometry. Three turbulator designs—full (FSFCT), semi (SSFCT), and hollow (HSFCT) shell-form cone turbulators—were analyzed to identify optimal configurations. Performance was assessed from both hydrothermal and economic perspectives using the performance evaluation criterion (PEC), levelized cost of energy (LCOE), and payback time. Results indicate that the configuration combining a semi-corrugated tube with a 1.5 mm radius, 3 % CuO nanofluid, and the FSFCT achieved a 369 % increase in Nusselt number, an LCOE of 0.546 $/kWh, and a payback time of 3.6 years, confirming its economic superiority. From a thermal-hydraulic perspective, the highest PEC value of 2.77 was obtained using the HSFCT under the same conditions.
Verifying hyperparameter sensitivities of optimal filter design methods for fault signature enhancement
Schmidt, Stephan; Wilke, Daniel Nicolas; Heyns, P.S. (Philippus Stephanus); Gryllias, Konstantinos C. (EDP Sciences, 2025-07)
Optimal filters are designed in vibration-based condition monitoring to enhance weak fault signatures for improved diagnosis. While optimisation-based filter design approaches have matured, their validation has typically focused on final objective values and constraint satisfaction. However, ensuring robust and reliable results requires verifying the correctness of design sensitivities, i.e., the gradients of both objective and constraint functions with respect to design variables, as well as hyperparameter sensitivities. This paper emphasises the importance of confirming and quantifying a filter’s response to varying hyperparameters to ensure it meets design specifications. By rigorously verifying sensitivities, engineers can more confidently deploy optimal filter designs that enhance fault-related features, resulting in more effective fault detection and diagnosis in complex engineering systems.
Innovating mobility : a student competition in wheel and track design
Chen, Devin; Sonalkar, Chaitanya Shekhar; Kikuta, Riku; Peenze, Andries Jacobus; Swamy, Varsha S.; Salmon, J. Ethan; Jelinek, Bohumir; Mason, George L.; Els, Pieter Schalk; Sandu, Corina (Elsevier, 2026-04)
In this paper, we propose an ISTVS Wheel/Track Design Student Competition to engage students in terramechanics through hands-on experience in off-road mobility design and testing. The competition will challenge student teams to design and fabricate a wheel or track system for a small unmanned ground vehicle (UGV), evaluated through tractive performance and mobility tests on selected soil types. By emphasizing low-cost, practical methods, the initiative ensures accessibility for students from diverse backgrounds. Teams can use free CAD software, 3D printing, or other rapid prototyping techniques to minimize expenses. The competition will feature two main components: a laboratory-style single-wheel test rig to assess tractive performance, and a small UGV platform for field-based mobility tests. Performance metrics may include drawbar pull, sinkage, slip, traction, and slope climbing, following ISTVS standards (He et al., 2020). Each competition will include design presentations and structured scoring criteria evaluating both design quality and performance. A standardized test matrix will assess structural integrity and functional performance. This initiative provides experiential learning opportunities, encourages innovation, and strengthens student engagement with ISTVS—cultivating the next generation of terramechanics engineers.
The influence of Prandtl number on the thermohydraulic behaviour of laminar mixed convective flow through horizontal tubes heated at a constant heat flux
Everts, Marilize; Omosehin, Oluwasegun S.; Van den Bergh, Wilhelm Johann (Elsevier, 2026-05)
The influence of Prandtl number on laminar mixed convective flow through a smooth, horizontal tube was investigated using ANSYS Fluent 22 to improve the understanding of the interaction between buoyancy and fluid viscosity on the thermohydraulic behaviour. Different propylene glycol concentrations (0%, 30%, 50%, 70%, 80%, and 90%) were considered for heat fluxes of 200-10 000 W/m2 and Reynolds numbers of 250-2000. The tube had an inner diameter of 5.1 mm and a length of 10 m. It was found that as the Prandtl number increased, the buoyancy force increased up to 74% for the 90% propylene glycol concentration compared to pure water, resulting in higher vorticity and circulation strength. However, this was confined near the tube wall and when quantifying the buoyancy effects using the secondary flow strength, viscosity-induced damping was found to decrease buoyancy effects by up to 95%. Conversely, for low-Prandtl number mixtures such as 0% and 30% propylene glycol concentrations, increased secondary flow thinned the thermal boundary layer and enhanced heat transfer by 40% and 28%, respectively, compared to forced convective flow, despite a lower buoyancy force. Furthermore, secondary flow strength was quantified and grouped into three distinct regions: (1) developing region, (2) suppression region, and (3) enhancement region. When viscous effects dominated at higher Prandtl numbers (70% and 90%), the velocity profile became skewed above the tube's centre, and the merging position of the hydrodynamic boundary layers shifted upwards, which is the opposite of the trend seen in fluids with lower Prandtl number (0%, and 30%). Furthermore, as the Prandtl number increased, the hydrodynamic boundary layers along the axis merge closer to the tube inlet, while the thermal boundary layers merge further downstream. HIGHLIGHTS • An increase in Prandtl number increased the buoyancy force but decreased buoyancy effects due to higher viscosities. • The vorticity magnitude increased with Prandtl number but was confined near the tube wall. • At high Prandtl numbers, the mixed convective velocity profile was skewed upward, shifting the peak velocity above the tube centre, while the opposite occurred at low Prandtl numbers. • The mixed convective temperature profile was skewed downward, causing the upper thermal boundary layer thickness to be greater than the bottom. • The hydrodynamic boundary layer merged earlier along the tube for increasing Prandtl number.
Experimental investigation of the effect of magnetic field placement on pressure drop, entropy generation, heat transfer, and thermal performance of Fe3O4/TiO2 magnetic nanofluids in turbulent flow
Adogbeji, Victor Omoefe; Govinder, Kuvendran; Sharifpur, Mohsen; Meyer, Josua P. (Elsevier, 2025-12)
Utilizing magnetic fields to manipulate fluid motion in ferrofluids has become a crucial approach for improving heat exchange efficiency in thermal applications, especially in pipe systems. This research conducts an experimental analysis of the effects of magnetic field (MF) patterns on heat transfer, entropy production, and the thermal efficiency of /Ti magnetic hybrid nanofluids (MHNFs) operating under turbulent flow regimes. Key parameters explored include nanoparticle concentration, effect of magnetic field placement, and signal waveform types (square, sine, and triangular). Results demonstrate that lower nanoparticle concentrations (0.0125–0.1 vol%) significantly improve thermal performance compared to deionized water and higher concentrations. The square waveform yielded the highest heat transfer enhancement (28.21 %), followed by sine (27.87 %) and triangular waveforms (22.81 %). Additionally, entropy generation was minimized through optimized magnetic field application and placement, highlighting its critical role in improving heat transfer efficiency. The thermal performance (TP) peaked at 26.33 % enhancement with 0.0125 vol%, while lower pressure drops were observed at 0.0125 vol% to be 7.67 %, and 0.00625 vol%, corresponding to 10.29 %. This study introduces a novel approach to optimizing heat transfer systems by integrating magnetic field waveform placement with precise nanoparticle formulations. The findings have significant implications for advancing energy-efficient cooling systems in thermal management applications, offering enhanced heat transfer with reduced energy losses.
Ride comfort optimization with handling constraints over rough terrain
Mahmood, Arslan; Kat, Cor-Jacques; Els, Pieter Schalk (Elsevier, 2026-04)
Semi-active suspension systems have garnered interest in addressing the trade-off between ride comfort and handling of off-road vehicles over rough terrain. This trade-off is challenging due to the on-road handling demand, with high ground clearance and center of mass complicating the matter further. Control strategies such as skyhook and ground-hook control might not be as effective due to the slow response time of the semi-active suspension system being investigated. This necessitates a different approach to leverage the semi-active suspension to improve vehicle ride comfort while maintaining acceptable handling. This study aims to find parameter settings of a semi-active suspension system for optimal ride comfort with a specified handling performance for a range of speeds and terrains, including rough terrains. Results show that optimal settings are relatively insensitive to road roughness but indeed sensitive to speed. Balancing of front and rear axle load transfer hold potential for improving handling without compromising comfort.
Designing and optimizing an intelligent self-powered condition monitoring system for mining belt conveyor idlers and its application
Jiao, Xuanbo; Wang, Zhixia; Wang, Wei; Gu, Fengshou (Springer, 2025-09)
Belt conveyors are extensively utilized in mining and power industries. In a typical coal mine conveyor system, coal is transported over distances exceeding 2 km, involving more than 20 000 idlers, which far exceeds a reasonable manual inspection capacity. Given that idlers typically have a lifespan of 1–2 years, there is an urgent need for a rapid, cost-effective, and intelligent safety monitoring system. However, current embedded systems face prohibitive replacement costs, while conventional monitoring technologies suffer from inefficiency at low rotational speeds and lack systematic structural optimization frameworks for diverse idler types and parameters. To address these challenges, this paper introduces an integrated, on-site detachable self-powered idler condition monitoring system (ICMS). This system combines energy harvesting based on the magnetic modulation technology with wireless condition monitoring capabilities. Specifically, it develops a data-driven model integrating convolutional neural networks (CNNs) with genetic algorithms (GAs). The conventional testing results show that the data-driven model not only significantly accelerates the parameter response time, but also achieves a prediction accuracy of 92.95%. The in-situ experiments conducted in coal mines demonstrate the system’s reliability and monitoring functionality under both no-load and full-load conditions. This research provides an innovative self-powered condition monitoring solution and develops an efficient data-driven model, offering feasible online monitoring approaches for smart mine construction.
Tyre tread estimation from 3D contact patch measurements on the inside of a deformed tyre
Kabutz, Thomas B.; Els, Pieter Schalk (Elsevier, 2026-01)
This study investigates the feasibility of using measurements of the geometry on the inner surface of a tyre to predict the geometry of the tread on the outside. The proposed method offsets the deformed inner surface along its normal directions by the tread thickness. Initially, a simple 2D cross-section model proved the feasibility of this method. This led to the development of a full 3D tyre model that can estimate the tread of a deformed tyre. Photogrammetry was used to capture a complete 3D geometry model of an unloaded and uninflated tyre, from which the inner and outer surfaces are used to calculate a displacement map for the model. Results indicate that the model can estimate the tread of both a SUV tyre and a large lug agricultural tyre to within about 2.5 mm of measurements of the deformed tread. This tyre is approximately 750 mm in diameter. The remaining error is likely due to the accuracy of the inner and outer surface measurements. The findings pave the way to predict soil volume displacement and contact area, providing crucial insights for vehicle control and mitigating environmental impacts in offroad scenarios. The system is expected to provide extremely useful data for future tyre-terrain interaction research.
Investigative studies on various metal loss flaws and their progression from a deep pinhole size to a lengthy size in pressurized tubes
Kalu, Ifeanyi Emmanuel; Inglis, Helen Mary; Kok, Schalk (American Society of Mechanical Engineers, 2025-12)
Localized metal loss (LML) in pressurized tubes is a primary contributor to tube failures and unplanned shutdowns in industrial boilers. Initially, these tubes may have inconspicuous anomalies introduced during manufacturing, testing, and inspection. Over time, as the vessels are deployed and exposed to harsh environmental, operating, or aging conditions, these anomalies evolve, eventually leading to their failure. In this paper, detailed investigative studies on various metal loss flaws were carried out to acquire insights on their failure behavior and mechanism, especially as they progress from very small size to lengthy size. Three investigations were carried out to identify which geometric parameters are most critical for predicting failure of the tubes and to what extent will they influence their failure. First, a range of real flaws that failed while operating under high internal pressure in a steam boiler were considered. The study compared two different modeling methods for evolving flaws to their failure geometry. The outcome shows that for most flaws, the failure evaluation is insensitive to the method of evolving the flaw to failure. Second, all the flaw geometries were modeled using the same material and operating conditions and their failure behavior studied. The findings show that failure pressure depends solely on the flaw thickness, and not on the other flaw dimensions, except for pinhole flaws. Finally, a range of flaw geometries, spanning the space from localized pinhole flaws to wide lengthy flaws, were investigated. Outcomes of these studies show that failure pressure for small flaws is sensitive to the flaw geometry. However, the failure pressure ceases to depend on the flaw length once the flaw length is greater than twice the tube diameter, and ceases to depend on the flaw width when the flaw length is greater than the tube diameter. These results suggest that gross plastic collapse is not the dominant failure mechanism for small flaws. However, for flaws with a length at least twice the tube diameter, the flaw dimension which predicts failure is the tube remaining thickness in the deepest part of the flaw. These studies establish the applicability limits of gross plastic collapse analysis for pressurized tubes experiencing metal loss and demonstrate opportunities for simplifying flaw analysis for sufficiently large flaws. Ultimately, the insights from this study will contribute toward appropriate preventive maintenance of these critical assets while in operation.
Development of a KPI-focused hybrid model for the Cummins QSB6.7 engine used in load haul dump vehicles
Louw, Bismarck; Heyns, P.S. (Philippus Stephanus); Schmidt, Stephan (inder, 2025-11)
Diesel engines are vital in mining operations, powering machinery in harsh environments where reliability is critical to avoid costly downtimes and economic losses. This study presents a hybrid model for the Cummins QSB6.7 turbocharged diesel engine to optimise predictive maintenance and operational efficiency in load-haul-dump vehicles. Controlled experiments generated key performance indicator (KPI) data under varied loads, capturing thermal, pressure, power, and efficiency metrics via QuantumX and CANedge2 systems. Physics-based models were calibrated using global and local optimisation, with complex metrics like turbocharger rotational speed as design variables. Neural networks mapped operational data, such as engine speed and load, to these variables, enabling accurate KPI predictions with minimal input. The model achieved MAPEs of 6.21% for thermal, 5.08% for pressure, and 4.12% for power, demonstrating strong predictive accuracy and practical applicability in mining contexts. These results underscore the model's potential to significantly reduce unplanned downtimes and associated economic losses.
Nanofluids mixed convection, heat transfer characteristics and effects of volume concentrations in the thermally developing region
Ibrahim, Ibrahim Umar; Sharifpur, Mohsen; Meyer, Josua P. (Elsevier, 2026-01)
Please read abstract in the article.
Sensitivity of the endwall flow in a linear vane cascade to blade fillet geometry
Shote, Adeola Suhud; Mahmood, Gazi (Elsevier, 2025-09)
Based on the blade chord and inlet velocity, the current computational study uses a linear vane cascade with a large filleted blade-endwall junction with a 2.01 x 105 Reynolds number. Three fillets with related profiles are explored. To evaluate the upshots of geometric differences in a fillet attached to the endwall flow-field, the height and endwall-width of the fillets are changed. The RANS k-ω turbulent model is used in the computations, and the results are compared to experimental results from a similar cascade without the fillet. The computed results of the secondary flow-field in the endwall region along the cascade are compared for baseline (no fillet) and filleted passages. As a result of diminished leading-edge and passage vortices, the fillets lower pitchwise pressure gradients, flow separation, axial vorticity, and overall pressure losses when compared to the baseline. The pros of fillets on endwall secondary flows are however unaffected by fillet's geometric changes.
Global challenges, local responses : exploring curriculum reform in South African engineering education
Wolff, Karin; Hattingh, Teresa; Smith, Lelanie (Wiley, 2025-07)
BACKGROUND AND AIM : There have been significant higher education curriculum reform initiatives over the past 30 years across different global regions in response to a range of drivers such as employability, global citizenship, and sustainability. In professions such as engineering, a key focus has been on holistic graduate attribute development for scarce skills needs in increasingly complex socio-technical sectors. This paper sets out to explore the drivers of engineering curriculum reform in higher education institutions (HEIs) in a Global South context. DESIGN/METHOD : Drawing on semi-structured, recorded focus group inter-views with 28 program coordinators and academics across 15 of the 16 HEIs offering engineering qualifications in South Africa, the research team set out to determine what kinds of curriculum reform initiatives were being under-taken, who was responsible for initiating, implementing, and supporting these initiatives, and what were perceived to be challenges and successes. The emergent drivers were framed in relation to curriculum responsiveness theory analyzed using an overarching “critical realist” framework with structure, culture, and agency dimensions that systemically influence how curriculum reform is constrained or enabled. RESULTS : The findings reveal both internal and external drivers that align with economic, institutional, and pedagogical responsiveness. The dominance of some levers over others is influenced by the underlying structural and cultural dimensions that affect agency. While some institutions show agency in curriculum reform, the dominant structure–culture dynamic often constrains innovation and maintains the status quo. CONCLUSION : The structure–culture–agency relationships that are presented high-light factors that constrain or enable curriculum reform, which has implications for practice and policy. To drive meaningful and sustainable reform, policymakers must develop frameworks that incentivize not only compliance with accreditation standards but also pedagogical innovation and social responsiveness, ensuring that curriculum transformation aligns with both economic demands and societal needs.
Thermos-aerodynamic performance and heat transfer analysis in a rectangular channel using various angle groove geometry
Aasa, Samson Abiodun; Mahmood, Gazi I. (Elsevier, 2025-09)
Please read abstract in the article.

Browse

Recent Submissions