Pusat Pengajian Kejuruteraan Aeroangkasa - Tesis
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- PublicationExperimental study of savonius turbines with tubercles inspired by the humpback whale concept.(2025-10)Sohib Abdelsattar Emam, Elsayed MareiThis study investigates the impact of tubercle configurations on the performance of Savonius turbines in low wind speed environments. In general, the Savonius turbine experiences negative torque on the returning blade due to flow separation and increased drag, which reduces overall torque output and power generation efficiency. Although Savonius turbines have a simple design, these aerodynamic challenges limit their overall performance. To address these issues, the current study explores the potential of tubercles, biomimetic features inspired by the fin of the humpback whale, to enhance turbine efficiency. The research utilized 3D printing to fabricate the turbine blade models, allowing precise control over tubercle configurations, including size, location, distribution, and peak variations. The blades were designed using SolidWorks and 3D printed with polylactic acid (PLA) for durability. Wind tunnel testing was conducted at a wind speed of 7 m/s, corresponding to a Reynolds number of 148,000, which represents low wind conditions typical of rural Malaysia. A parametric approach was used to evaluate turbine performance with various configurations, including variations in tubercle location (center and edges), distribution, size, and peak variations (gradual and uniform). The findings demonstrate that tubercle configurations significantly influenced turbine performance, with the most notable improvements observed in configurations with larger tubercles placed centrally (D1). These larger tubercles optimized boundary layer control, reduced drag on the returning blade and enhanced vortex generation, resulting in a marked increase in torque and power coefficients. Configurations with peak variation (D1 and N3) further stabilized the flow by improving vortex shedding and reducing turbulence, which enhanced turbine efficiency. In contrast, smaller or uniformly distributed tubercles (N1 and N2) showed limited improvements in drag reduction and torque production. The study also revealed that partial tubercle coverage (D1 and D2, with 67% coverage) outperformed full coverage configurations (A1W1 and N4), which caused higher turbulence and lower performance due to excessive disruption of airflow. Overall, the study emphasizes that a strategic combination of tubercle size, location, distribution and peak variation can significantly improve torque generation and turbine efficiency. These findings highlight the potential of tubercle modifications to optimize Savonius turbines for low wind speeds, laying the groundwork for more efficient renewable energy solutions in remote, off-grid areas.
- PublicationInvestigation on the fire resistance and reaction properties of woven jute fibre reinforced epoxy composites.(2025-10)Siti Rodiah binti Mohd KassimThe increasing demand for sustainable and environmentally friendly materials in various industries has driven the exploration of Natural Fibre Composites (NFCs). However, challenges remain in understanding their fire performance under fluctuating thermal and fire conditions. This study uniquely integrates the evaluation of fire resistance and fire reaction of woven jute fibre-reinforced epoxy composites over a broad range of elevated temperatures and heat fluxes, combining mechanical testing, cone calorimetry, and statistical modelling with correlation matrix analysis to quantify and elucidate relationships between fire performance parameters. Samples are fabricated using a hand lay-up process followed by vacuum bagging. For fire resistance, tensile and flexural tests are conducted at temperatures from room temperature (RT) to 250 °C. Tensile strength declined from 54.48 MPa to 42.95 MPa at 60 °C, while flexural strength decreased from 65.38 MPa at RT to 24.97 MPa (a 40 % reduction). Significant degradation occurred beyond 100 °C. For fire reaction, cone calorimetry at heat fluxes of 35, 50 and 70 kW/m² showed time to ignition reduced from 67 s at 35 kW/m² to 13 s at 70 kW/m², peak heat release rate increased from 334.0 kW/m² to 513.3 kW/m², and total smoke production rose by 21 % at the highest heat flux. Statistical analysis using One-Way ANOVA confirmed the significant effects of temperature and heat flux (p < 0.05) on fire performance. Regression models successfully predicted fire reaction parameters at intermediate heat flux levels, demonstrating their potential as predictive tools for estimating composite behaviour under varying fire exposure scenarios. Pearson correlation coefficients revealed strong positive correlations between heat flux and heat release rate (r = 1.00), and strong negative correlations with ignition time (r = -1.00), indicating that as heat flux increases, composites ignite faster and release heat more intensely. These findings provide quantitative performance thresholds and underscore the importance of considering heat flux when assessing fire risk and mechanical performance, thereby guiding safer material selection and design for applications such as low-temperature load-bearing panels, automotive and aerospace interiors structures (door panels, dashboard supports and seat backs) and building components (wall cladding, insulation panels and partition boards). To extend usability in thermally demanding or fire-prone environments, material odifications such as fire-retardant additives or hybrid reinforcement are recommended.
- PublicationMachine learning-based image processing and iot-based monitoring system for disease detection in harumanis mango plantations.(2025-11)Sheikh Mohamad Naim bin Shikh ShatirLocal farmers face multiple challenges in managing Harumanis plantations. The effect of Movement Control Order (MCO) has restricted farmers from closely supervising their crop plantation, while, the lack of utilization of smart farming (SF) devices among farmers in Malaysia is due to the high cost of such devices. Consequently, many farmers persist with evaluating soil nutrient and disease recognition using traditional method, while new farmers in particular, struggle to differentiate crop diseases due to limited agricultural knowledge. The goals of this research are to develop a cost-efficient, IoT-based monitoring system with image processing algorithm, evaluate parallel image processing techniques, decide the most suitable algorithm for leaf disease detection supported by analyzed results and correlate extracted feature patterns for corresponding leaf diseases with nutrient parameters—temperature, moisture, and nitrogen, phosphorus and potassium (NPK) values, obtained from sensors. The sensors are connected to an ESP8266 microcontroller, in which the data are transmitted through wireless communication to a Raspberry Pi (RPi) microprocessor. A custom camera attached to the RPi will provide image of the Harumanis mango plant, where the images are processed using Open Computer Vision (OpenCV) library for detection and classification of nutrient deficient disease affecting the Harumanis mango plant. Additionally, the Normalized Difference Vegetation Index (NDVI) value is analyzed. Furthermore, a graphical user interface for Internet of Things (IoT) system is built and accessible from end-devices, for crop monitoring. The IoT system is integrated with parallel processing for Harumanis mango leaf diseases detection, using YOLOv8 model, trained on custom dataset. The system incorporates machine learning object-detection algorithm, capable in extracting harumanis leaf diseases features— anthracnose, leaf burn, and healthy leaves. The ML performance trained with augmented dataset improved the detection by 14% for anthracnose, 5% for healthy and 3% for leaf burn. Using logistic regression (LR), the system performed correlation analysis based on leaf disease count and sensor parameters (temperature, humidity, soil moisture and NPK). The model then predicted that a healthy Harumanis mango plant, under experimental conditions of this study, have nitrogen value of 30 mg/kg, phosphorus is 47 mg/kg and potassium is 125 mg/kg. These values were based on the correlation analysis between extracted Harumanis mango leaf disease counts and sensor measurements collected during field trials, ensuring that the nutrient thresholds are derived directly in this research dataset than assumed from literature.
- PublicationFatigue failure analysis of CFRP composite laminates using modified stiffness degradation method.(2025-05)Nabilah binti AzinanCarbon fibre reinforced polymer (CFRP) composite laminates have been extensively utilised in various industrial applications due to their outstanding mechanical properties. In this study, the stiffness degradation behaviour of CFRP laminates subjected to cyclic loading conditions was analysed using two analytical models: the Modified Stage I model and the modified Stage I to Stage III model. Both models were developed based on the original model proposed by Lurie and Minhat, and subsequently enhanced through the introduction of several specific parameters to improve the predictive accuracy between analytical results and experimental data. The application of a linear elastic model facilitated the determination of the mechanical properties of the CFRP materials, which served as input parameters for the modified models. The modified Stage I model was employed to evaluate stiffness degradation during the initial damage phase, particularly matrix cracking. The resulting analytical stiffness degradation curves were compared with the experimental curves. Subsequently, the modified Stage I to Stage III model was applied to assess the full spectrum of stiffness degradation, encompassing damage evolution from the initial stage to the final stage, including fibre breakage. To evaluate the accuracy of both models, the percentage difference between the analytical model and experimental data was calculated for all three CFRP laminate configurations investigated in this study, namely [0,±45]s, [0,902]s, and [0,90,±45]s. Overall, the findings indicate that the Modified Stage I model offers the highest predictive accuracy when directly compared with experimental data, particularly for early-stage damage. The simplicity of its formulation and its strong agreement with empirical results render it highly effective and reliable for predicting fatigue-induced damage in the initial service life of the structure. However, to provide a more comprehensive representation of the material’s stiffness degradation behaviour throughout its service life, the modified Stage I to Stage III model presents a balanced compromise between predictive accuracy and the ability to capture the complete damage progression. Therefore, the selection of the most appropriate model should be guided by the intended application. For short-term assessments or early-stage damage monitoring, the Stage I model is the most suitable. Conversely, for long-term durability predictions involving comprehensive structural integrity evaluation, the Stage I to Stage III model is more appropriate, as it demonstrates a high level of accuracy and inclusiveness that closely aligns with experimental observations.
- PublicationExperimental and numerical study on aerodynamic characteristics of wind turbine blades with spoiler active flow control mechanism.(2025-12)Mohd Hafiz Bin Ab SatarThe integration of flow control methods in turbines has emerged as a pivotal approach to improve aerodynamic efficiency and, consequently, energy output. Therefore, the current study aims to introduce an active flow control mechanism using a spoiler to improve the performance of a wind turbine blade. Initially, the airfoil and spoiler were fabricated and subsequently tested in a wind tunnel. The resulting experimental setup served as a benchmark for developing the numerical model. The results of the developed simulation models showed an acceptable agreement with the experimental data. Further studies were carried out using the validated model to analyze the effect of multiple geometric and operating parameters of the spoiler and airfoil. It was found that the new spoiler design had higher performance than both the other new and present designs. However, the performance was still 71.9% lower than the baseline airfoil. Further analyses found that the best performance was achieved with a spoiler gap, size and location of 0.0005c (-71.8%), 0.06c and 0.0065c (-31.4%), and 0.9c (1.4%), respectively. Regarding operating conditions, the best amplitude, frequency, and wind speed were set to 12.5°, 1.25 Hz, and 6 m/s, respectively, reaching improvements of up to 8.56%. The active spoiler was revealed to have a higher performance when attached to the NACA-airfoil (1.6%) compared to the DU-airfoil, GOE-airfoil, FX airfoil and S-airfoil.