https://ir.unisa.ac.za/handle/10500/27464 Thu, 20 Aug 2026 23:29:46 GMT 2026-08-20T23:29:46Z https://ir.unisa.ac.za/handle/10500/32947 Modelling of the fluid structure interaction of the horizontal axis bio-inspired wind turbine blade and effect on annual energy production Netshivhulana, Arinao Glory In response to South Africa’s ongoing energy crisis, the exploration of renewable energy technologies has become increasingly urgent. Wind energy, as one of the fastest growing renewable sources, offers significant potential for sustainable power generation. In this study, performance improvement of Horizontal Axis Wind Turbines (HAWTs) was explored by employing a bio inspired blade design method. To improve the aerodynamic efficiency, inspired by the aerodynamically efficient wing shape of the albatross, a corrugated version of the GOE174 airfoil was designed. The original airfoil geometry was rebuilt from NACA data and methodically adjusted by amplitude functions for generating corrugations. The resulting 2D profile was extruded in Solid Edge to get a full 3D blade model and then analyzed with ANSYS Fluent 2025R1. Computational fluid dynamics (CFD) simulations were performed using the k-ω SST turbulence model to examine the lift and drag characteristics over a wide variety of angles of attack. The main goal was to investigate the potential of bio-inspired corrugation to boost the aerodynamic efficiency compared to smooth blade. The results revealed that corrugated geometry always have higher drag but offer better lift-to-drag ratios at low angles of attack, particularly around 2.71 m/s where stall delay is noted. The corrugated airfoil performs similarly at 3.47 m/s, with a marginal edge at 20° angle of attack, with a power coefficient (Cp) of 0.466 relative to 0.459 for the smooth profile. Analysis of the Annual Energy Production (AEP) showed a small but measurable increase of 1.4%: 16.753 kWh/year for the corrugated blade compared to 16.518 kWh/year for the smooth blade. These efficiencies are minor but important to long term turbine operating in low to moderate wind environments. The results demonstrate the promise of bio-inspired corrugated patterns for HAWT performance improvement, tying computational modelling to experimental applicability, and emphasize the relevance of biomimicry in the development of renewable energy technology. Error comparison between CFD and wind tunnel experiments indicated good agreement at low velocity (σ = 0.156), considerable variability at 3.47 m/s (σ = 0.322) and significant disparities at 5.36 m/s (σ = 0.908). The corrugated airfoil showed better lift stability, stall delay and higher efficiency, which is beneficial for the practical application in HAWTs. Abstract and text in English Fri, 01 May 2026 00:00:00 GMT https://ir.unisa.ac.za/handle/10500/32947 2026-05-01T00:00:00Z https://ir.unisa.ac.za/handle/10500/32535 Design optimisation and development of a pneumatic prosthetic foot Godlimpi, Zanodumo Thandazani Lower-limb amputation is a life-saving and life-changing surgery that significantly impacts mobility and quality of life, particularly in South Africa, where access to advanced prosthetic technology is hindered by socio-economic factors and infrastructure challenges. Prosthetic feet are classified into three distinguishable categories: conventional feet, which include solid ankle cushion heel and articulated prosthetic feet, energy storage and release feet and bionic feet. Conventional passive prosthetics, such as the SACH foot, often fall short in replicating the normal walking dynamics, leading to asymmetries when walking and increased energy cost of walking. This study piloted a pneumatic prosthetic foot to investigate the biomechanical benefits of using this innovation while walking at self-selected walking speed over flat surfaces. The study utilized a quantitative (experimental) research method, commencing with the Finite Element Analysis (FEA), using the ANSYS software to simulate axial structural loads during standing positions on titanium and aluminum alloy shank segments. A prototype was developed featuring a crank-slider mechanism and a pneumatic cylinder to modulate ankle stiffness. Clinical evaluation involved a case study of two transtibial participants. Walking gait was analysed using the Templo markerless motion capture system (Theia3D) across three conditions: the prescribed passive prosthetic foot, an unpressurized version of the pneumatic prosthetic foot, and a pressurized version of the pneumatic prosthetic foot (4 bars). Spatiotemporal parameters, kinetics, and kinematics, including stride length, cadence, and vertical ground reaction forces (vGRF), were systematically recorded and analyzed across varying conditions. A stark contrast between participants was revealed by the study findings, participant 1 demonstrating improvements in walking symmetry (spatiotemporal parameters and kinetics), while participant 2 demonstrated minimal benefit when using the pneumatic prosthetic foot. The study findings suggest that device performance, one way or another, was influenced by the user adaptation and biomechanical conditions of the participant. The preliminary findings align with the broader body of literature, suggesting that semi-active prosthetic devices can bridge the gap between expensive powered devices and passive prosthetics. On the contrary, the pneumatic prosthetic foot was not practically lighter than other powered prosthetic devices. This research developed a functional pneumatic prosthetic prototype that can withstand the axial loading of the human body, and can be used for mobility. Though the pneumatic prosthetic prototype has demonstrated potential, the findings need to be interpreted with caution due to the small sample size (n=2), which limits the generalizability of the findings. The current pneumatic prosthetic foot prototype requires further refinements to reduce both the mass and the height of this prosthetic foot. Also, improvements in the control system are required to modulate the ankle stiffness during walking. Additionally, the system faced challenges in replicating passive shock absorption during the load acceptance phase in the early stance. Future research should include large and diverse participant cohorts, and longitudinal studies to monitor neuromuscular adaptation and changes in the walking dynamics. Text and abstract in English Wed, 27 May 2026 00:00:00 GMT https://ir.unisa.ac.za/handle/10500/32535 2026-05-27T00:00:00Z https://ir.unisa.ac.za/handle/10500/32428 Deep learning for spatial multi-omics: predicting cardiomyocyte differentiation efficiency at single-cell resolution Kgabeng, Tumo Cardiovascular diseases remain the leading cause of global mortality, with limited regenerative capacity of adult cardiac tissue presenting significant therapeutic challenges. The primary cause of death worldwide is still cardiovascular diseases, and treating these conditions is extremely difficult due to the adult heart tissue's limited capacity for regeneration. Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC CMs) present promising potential for cardiac regenerative medicine; however, existing differentiation protocols are highly inconsistent and do not have accurate predictive evaluation techniques. By integrating the analysis of temporal gene expression data and spatial transcriptomics, this study developed a novel hybrid deep learning architecture that combines Graph Neural Networks (GNNs) and Recurrent Neural Networks (RNNs) to predict the outcomes of cardiomyocyte differentiation. RNN components analysed temporal gene expression trajectories across 800 samples and 10 time points, while GNN components processed spatial transcriptomics data from 752 tissue spots to capture spatial relationships. Three fusion strategies - concatenation, attention-based, and ensemble approaches - were meticulously evaluated. With an accuracy of 96.67%, the ensemble fusion approach outperformed the state-of-the-art computational approaches by a significant margin (+13.47% compared to the top GNN approaches and +6.97% compared to specialised biological models). Keywords: Cardiomyocyte differentiation; Spatial transcriptomics, Spatial multi-omics; Single-cell biology; Deep learning; Graph Neural Networks; Recurrent Neural Networks; Stem cells; Artificial Intelligence; Cardiac biology Fri, 06 Mar 2026 00:00:00 GMT https://ir.unisa.ac.za/handle/10500/32428 2026-03-06T00:00:00Z https://ir.unisa.ac.za/handle/10500/32332 Estimating brittleness indexes from mechanical and petrographic characteristics of Norite Molomo, Selaki Grace Norite is a coarse-grained plutonic rock that has been relatively understudied in terms of its mechanical and petrographic properties. This study investigates the brittleness of norite within the Eastern Limb of the Bushveld Igneous Complex (BIC), South Africa. However, there is a scarcity of studies that quantitatively link its petrographic characteristics to establish brittleness indices. The primary aim was to estimate brittleness indexes based on both mechanical and petrographic properties of norite, which is a significant rock type commonly found in the hanging walls of platinum mines. Given the recurring safety incidents, especially falls of ground and rock bursts in underground mining, understanding the brittleness of norite is essential for enhancing geotechnical designs and safety measures. Samples were collected from a 10-meter exposure along Mototolo Road in the Critical Zone of the Eastern Bushveld Complex, near the Anglo-American Platinum Mototolo Mine. Mechanical analysis involved laboratory testing, which includes uniaxial compressive strength (UCS), tensile strength, Young's modulus, and Poisson’s ratio, supported by numerical simulations and multivariate regression models. The results indicate that norite exhibits high compressive strength and low ductility, with brittleness indexes effectively predicted using combinations of strength parameters. Mineralogical investigations were done using thin-section petrography to evaluate grain texture, contact nature, and mineral composition. It was observed that coarse and medium grain textures significantly influence brittleness, whereas grain contact type alone lacks predictive power. The main contribution of this work is the development of integrated predictive models that use both mechanical and mineralogical data. While the use of surface samples presents a limitation, their geological equivalence to underground norite supports the relevance of the findings for subsurface application. The findings enhance the understanding of the structural performance of norite and suggest practical recommendations for underground mine design. This research further contributes to improved and safer mining operations. Fri, 13 Feb 2026 00:00:00 GMT https://ir.unisa.ac.za/handle/10500/32332 2026-02-13T00:00:00Z