Tanzania Journal of Engineering and Technology

Condition Optimization for the Synthesis of Castor Oil Templated Mesoporous Silica

2025-10-03T09:47:09+00:00

The present work provides suitable conditions for the synthesis of mesoporous materials with improved porosity using an optimization technique. The proposed preparation method involves forming final products by varying the amount of castor oil, media, and template removal. The obtained samples were examined by TGA, XRD, DRIFT and nitrogen physisorption studies. It was observed that the porosity of the obtained samples was dependent on the conditions under which the materials were synthesized. All synthesized materials showed the Type IV adsorption-desorption isotherm features of mesoporous, regardless of the conditions utilized during the synthesis. The sample synthesized using 2.5 g of a castor oil template in acidic media and calcination as a
template removal, displayed the highest BET surface area of 906 m2/g, pore volume of 1.44 cm3/g and a pore diameter of 6.5 nm. When reflux was used as a template removal technique on materials synthesized under the same conditions, the surface area was 900 m2/g with a pore volume of 1.4 cm3/g and a pore diameter of 6.6 nm. Even though the latter sample exhibited less surface area, it is still better than the former sample since the template removal by reflux is a greener technique than the removal through calcination. XRD results showed that no peak was observed in low-angle implying that the materials lack long-range order of the pores. This large surface area synthesized mesoporous materials are potential adsorbents or catalytic supports. Therefore, the present study promotes the production of eco-friendly materials using castor oil, a biodegradable and renewable resource, as a pore-directing agent

CNN-Based Hybrid Model for Detecting Blight Diseases in Potato Crops with Advanced Image Processing Techniques

2025-10-03T12:12:50+00:00

Potato production plays a vital role in global agriculture as a major food source for large populations. However, potato crops are highly susceptible to diseases, particularly Early Blight and Late Blight, which result in substantial yield losses. Timely detection and effective control of these diseases are essential for maintaining stable crop output. This study explores the integration of Convolutional Neural Networks (CNNs) and advanced image processing techniques to differentiate between diseased and healthy potato plants accurately. Two datasets comprising original and enhanced images were used to train four CNN models: InceptionV3, Xception, Densenet201, and Resnet152V2. The original images underwent background removal only, whereas the enhanced images were further processed using contrast enhancement and morphological transformation in addition to background removal to reduce noise, improve quality, and prepare the images for analysis. The CNN models were trained using these datasets, with their bottom layers fixed and the top layers fine-tuned to improve performance and reduce training time. Experimental results revealed that models trained on enhanced images achieved a 2.45% to 4.45% improvement in accuracy, precision, and sensitivity compared to those trained on original images. Moreover, a hybrid model that combined two high- performing CNNs achieved a 98.91% accuracy, marking up to 10.69% improvement over individual models. This approach offers significant potential for reducing crop yield losses while minimizing dependence on chemical treatments.

Investigating the Harmonic Content of a PWM Inverter with Varying Modulation Index

2025-10-03T10:07:24+00:00

Photovoltaic energy is a clean and endless vital renewable energy. In order to generate electricity from solar energy an inverter is required to transform the direct current into alternating current. Also, with the emerging of new ultra-high voltage direct current transmission technology, the rectification and inverters play a great role. Most three phase two-level inverters draw harmonics that cause heat dissipation, waveform distortions hence affect the electrical loads. Knowing that Total Harmonic Distortion content of voltage source inverter is important and must be within the allowable range. Several schemes are suggested to mitigate the distortion in order to produce as much a sinusoidal output signal as would be possible. The most widely used control process of the semiconductor switches is Pulse Width Modulation technique. One of such schemes is using a Sinusoidal Pulse Width Modulation -based inverter which is usually used in inverters for industrial applications. In this paper, a study of the performance of the SPWM technique is presented for a three-phase H-bridge inverter and the simulation results obtained in MATLAB/Simulink demonstrate that the significantly investigation on the harmonics when varying the modulation index. These results confirm that the total harmonic distortion factor of the inverter output voltage decreases as the modulation index increases as a result, reduces the waveform distortion rate and suppresses the effects of harmonics. This is of great significance for the safe, stable, and efficient operation of the power system.

Techno-Economic Analysis of Hybrid PV-Wind-Diesel Generator Swarm Grid for Rural Electrification in Tanzania

2025-10-03T10:19:36+00:00

Remote, rural, and off-grid communities, particularly in Sub-Saharan Africa (SSA), face significant challenges in securing reliable and
affordable electricity. While solutions such as solar home systems (SHSs) and diesel generators (DGs) have been adopted by some
individuals, their deployment is often not optimized to meet the full load demand. This study addresses this challenge by proposing a hybrid swarm grid (HSG) design that integrates photovoltaic (PV), wind energy, and diesel generators (DGs). Utilizing MATLAB/Simulink and HOMER, the HSG is modeled and optimized for a typical SSA village, incorporating real-world variables such as load demand profiles, solar irradiance, and wind patterns. A comprehensive techno-economic analysis is conducted to evaluate the feasibility and effectiveness of the proposed system, taking into account equipment, fuel, and maintenance costs. The HSG configuration yields a Levelized Cost of Energy (LCoE) of €0.123 /kWh (TZS 344.4 /kWh), which is significantly lower than the
average LCoE of €0.375 /kWh (TZS 1,050 /kWh) for individual systems. This highlights the potential of hybrid-based swarm grids to
deliver cost-effective energy solutions, even in applications with high demand from multiple consumers. Furthermore, this research provides strong evidence for prosumers to invest in renewable-based swarm grids over conventional diesel generators, which exhibit higher Net Present Costs (NPC), LCoE, and environmental impact.

Maximum Likelihood Symbol Timing Algorithm Based on Cyclic Prefix for OFDM Systems

2025-10-03T10:27:19+00:00

In this paper, a blind symbol synchronization algorithm is presented for orthogonal frequency-division multiplexing (OFDM) systems, and a timing function based on the redundancy of the cyclic prefix (CP) is introduced. The existing algorithms rely on the prior knowledge of the channel energy distribution i.e. channel power profile. In practical environment the channel power profile is unknown to the receiver and its statistics are expected to be highly changing. Nevertheless, the use of pilot symbols in channel profile estimation reduces efficiency as data subcarriers are used to carry pilots instead of payload. In this paper a timing function that accounts for early and late timing introduced errors together with channel estimation errors is introduced. The effects of symbol timing errors are quantified and an optimal OFDM symbol timing solution is derived using modified maximum likelihood
(ML) method. Compared with existing schemes in the literature, the proposed approach does not rely on explicit detection of individual channel paths or the delay spread boundary and therefore greatly reduces timing complexity. The main contribution lies in modifying the ML metric to jointly account for intercarrier interference (ICI), inter symbol interference (ISI), and channel estimation error, leading to improved robustness in dispersive channels without requiring prior channel knowledge. Simulation results show that the proposed algorithm is robust and outperforms the existing CP-based algorithms, particularly in double dispersive channels, achieving up to 5 dB NMSE improvement, lower BER at low SNR, and a 33% reduction in computational complexity

Optimal Location and Sizing of FACTS Devices to Improve Voltage Profiles on a 132 kV Mwanza-Musoma-Nyamongo Transmission Line

2025-10-03T11:46:11+00:00

Recently, utility companies have desired to supply quality, stable and
reliable power to customers, and ensure they meet the demand. Flexible
AC Transmission Systems (FACTS) dynamic compensator devices such as Static Synchronous Compensator (STATCOM), Static VAr
Compensator (SVC) and Unified Power Flow Controller (UPFC) are an impeccable choice, however, cost is one of the limiting factors
following these technologies. In addition, using FACTS devices in the system requires a detailed steady state, dynamic and optimisation analysis to effectively meet the purpose and ensure reduced cost. This paper proposes using an optimised FACTS device to improve voltage profile, power transfer, system stability, and reduce system losses on 132 kV Mwanza–Musoma–Nyamongo transmission line. The analytical and Particle Swarm Optimisation technique was used to obtain the FACTS device's optimal size and location. The optimized FACTS device is incorporated in the system model and implemented using PSS/E software version 35. The model was analysed with the 132 kV Mwanza Musoma–Nyamongo transmission line loaded to its capacity, the network was observed to have an improved voltage profile, the voltage deviation lowered by 84% as compared to the current network voltage
deviation of 0.2 p.u. Also, the transmission line transfer capability increased by 32 MW from the current transfer capability without
distortion of the voltage profile and with an improvement on system stability. The ± 60 MVAr optimized STATCOM was observed to lower the system losses by an average of 14%. Furthermore, analysis concerning with the operation costs was observed that with maximum transfer the FACTS device investment payback period is thirteen (13) months demonstrating the system's financial viability