School of Engineering (SEng.) Collections

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https://makir.mak.ac.ug/handle/10570/180

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Now showing 1 - 5 of 374
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    Investigating the influence of masonry infill walls on the seismic response of reinforced concrete frame structures in Uganda
    (Makerere University, 2026) Kakuru, Verny Baguma
    This study investigates the influence of masonry infill walls on the seismic response of Reinforced Concrete frame structures in Uganda, where current seismic design codes lack explicit provisions for infill wall and RC frame interactions. The study develops a site-specific design response spectrum for Uganda’s highest seismic zone. Finite element modelling in ABAQUS was employed to simulate the detailed nonlinear in-plane behaviour of infilled and bare RC frames. For broader parametric studies across varying building heights and infill types, like, clay bricks and solid concrete blocks, the equivalent diagonal strut method was implemented in ETABS. Model validation was conducted against established experimental results from pseudo-dynamic tests, ensuring accuracy in displacement, drift, and base shear predictions. Nonlinear static pushover analyses were performed to evaluate seismic performance indicators, including lateral displacement, storey drift, base shear capacity, and stiffness contribution. Results indicate that concrete block infills, owing to their higher compressive strength, provide greater initial stiffness and higher base shear capacity than clay brick infills. However, stiffness contribution decreases with increasing building height, reducing the relative benefit of infills in taller frames. Infill walls significantly reduced displacement and storey drift across all configurations, while Base shear was increased. Displacement was reduced by 80% for the concrete infill in the 2-storey structure and by 73 % for the clay infill. However, the stiffness contribution decreased as building height increased. This is observed by concrete infill reducing displacement by 79.7% in a 2-storey structure, but reducing it by 50% in a 10-storey structure. This research, therefore, provides region-specific evidence for the inclusion of masonry infill effects in seismic design.
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    Encapsulated and non-Organic Fertilizers for water retention and controlled nutrient release.
    (Makerere University, 2026-02) Nantambi, Hadijah
    Declining soil fertility, low nutrient-use efficiency, and heavy dependence on imported synthetic fertilizers remain critical constraints to agricultural productivity in Uganda. This research developed and evaluated advanced organic fertilizers derived from biochar-blended compost (BBC), specifically focusing on two engineered derivatives: Encapsulated Biochar-Blended Compost (EBBC) and Nano-Biochar-Blended Compost (Nano-BBC). An optimized co-composting matrix (60% Tithonia diversifolia and 5.7% rice husk biochar) was established using Response Surface Methodology and Central Composite Design. The quadratic models developed for nitrogen, phosphorus, and potassium were highly significant (F-values of 33.70, 50.64, and 86.60, respectively) and exhibited a non-significant lack of fit (p < 0.05). Model robustness was confirmed by high coefficients of determination (R2 ≥ 0.97) and adjusted R2 ≥ 0.94, and low coefficients of variation (3.24%–6.24%), indicating high reproducibility. Tithonia diversifolia most influenced N and K enrichment, while P availability depended on quadratic effects of both substrates. The enriched mature compost served as the base for enhancements. Nano-BBC synthesis was optimized via high-energy ball milling, and a reduced quadratic model identified the milling solvent mass and ball-to-powder ratio as key factors for particle size reduction. Chitosan–starch biopolymer encapsulation further enhanced performance. Under simulated 20-mm rainfall, EBBC reduced leachate volume to 6.5 mL (65% less than conventional BBC and mineral fertilizers) while eliminating nitrate-N leaching. Nitrogen-release assays showed controlled release: EBBC pellets released 56.9–70% of total N over 30 days via Fickian diffusion, unlike uncoated BBC, which exceeded 100% by day 25 via non-Fickian kinetics. EBBC also improved soil moisture retention in sandy loam to 4.4% at 30 days via hydrogel effects. In semi-field Zea mays L. (Maize) trials under drought, EBBC produced the highest plant height and shoot biomass, outperforming BBC, Nano-BBC, and synthetics. All formulations met FAO/EU heavy-metal thresholds. This scalable, climate-smart framework transforms organic waste into high-performance fertilizers, synchronizing nutrient delivery with drought resilience in Uganda.
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    Encapsulated and nano-organic fertilizers for water retention and controlled nutrient release.
    (Makerere University, 2026) Nantambi, Hadijah
    Declining soil fertility, low nutrient-use efficiency, and heavy dependence on imported synthetic fertilizers remain critical constraints to agricultural productivity in Uganda. This research developed and evaluated advanced organic fertilizers derived from biochar-blended compost (BBC), specifically focusing on two engineered derivatives: Encapsulated Biochar-Blended Compost (EBBC) and Nano-Biochar-Blended Compost (Nano-BBC). An optimized co-composting matrix (60% Tithonia diversifolia and 5.7% rice husk biochar) was established using Response Surface Methodology and Central Composite Design. The quadratic models developed for nitrogen, phosphorus, and potassium were highly significant (F-values of 33.70, 50.64, and 86.60, respectively) and exhibited a non-significant lack of fit (p < 0.05). Model robustness was confirmed by high coefficients of determination (R2 ≥ 0.97) and adjusted R2 ≥ 0.94, and low coefficients of variation (3.24%–6.24%), indicating high reproducibility. Tithonia diversifolia most influenced N and K enrichment, while P availability depended on quadratic effects of both substrates. The enriched mature compost served as the base for enhancements. Nano-BBC synthesis was optimized via high-energy ball milling, and a reduced quadratic model identified the milling solvent mass and ball-to-powder ratio as key factors for particle size reduction. Chitosan–starch biopolymer encapsulation further enhanced performance. Under simulated 20-mm rainfall, EBBC reduced leachate volume to 6.5 mL (65% less than conventional BBC and mineral fertilizers) while eliminating nitrate-N leaching. Nitrogen-release assays showed controlled release: EBBC pellets released 56.9–70% of total N over 30 days via Fickian diffusion, unlike uncoated BBC, which exceeded 100% by day 25 via non-Fickian kinetics. EBBC also improved soil moisture retention in sandy loam to 4.4% at 30-days via hydrogel effects. In semi-field Zea mays L. (Maize) trials under drought, EBBC produced the highest plant height and shoot biomass, outperforming BBC, Nano-BBC, and synthetics. All formulations met FAO/EU heavy-metal thresholds. This scalable, climate-smart framework transforms organic waste into high-performance fertilizers, synchronizing nutrient delivery with drought resilience in Uganda.
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    Development of an Efficient Path Planning Algorithm for Unmanned Aerial Vehicles - Wireless Sensor Networks in Agricultural Data Collection
    (Makerere University, 2026) Oswaha Matthew Joseph Odiongo
    The increasing demand for precision agriculture has intensified the need for efficient data collection methods across expansive farmlands. This research focuses on the development of an efficient path planning algorithm for Unmanned Aerial Vehicles (UAVs) deployed in Wireless Sensor Networks (WSNs) to facilitate timely and energy-efficient agricultural data collection. The study proposes and evaluates a Particle Swarm Optimization (PSO)-based algorithm to optimize UAV trajectories concerning multiple conflicting objectives, including minimizing mission completion time, reducing energy consumption, and maximizing coverage efficiency through minimizing UAVs’ flight paths. A simulation model was implemented in Matrix Laboratory (MATLAB), considering realistic constraints such as UAV energy limits, communication range, sensor clustering, and agricultural field geometry. The performance of the developed algorithm was compared against the spherical particle swarm optimization algorithm (SPSO), Genetic algorithm (GA), and Random computation method (RCM). Results demonstrate that the developed PSO-based algorithm significantly outperforms others in terms of path length reduction, energy utilization, and mission completion time while maintaining high data collection accuracy. The findings validate the effectiveness of evolutionary optimization techniques in improving UAV-based WSN operations for precision agriculture, outperforming the benchmarking algorithms, with an average optimization efficiency over all the metrics of 23% compared to the random computation method (RCM) as the baseline algorithm. This work contributes a scalable and adaptable algorithmic approach suitable for real-world deployment in resourceconstrained agricultural environments.
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    Modelling the effects of road Geometric design on vehicle emissions.
    (Makerere University, 2026) Itaaga, Emmanuel
    The transport sector is a major contributor to global greenhouse gas emissions, with road transport accounting for nearly 20% of the total CO₂ emissions. In Uganda, rapid traffic growth, reliance on fossil fuels, and declining air quality have intensified environmental and health challenges. Existing emission models, developed mainly for high-income countries, rely on advanced data and modern vehicles, limiting their applicability to Uganda’s older and diverse vehicle fleet. The absence of locally adapted models that integrate road geometry and traffic dynamics constrains the development of sustainable transport infrastructure. This study developed and validated mathematical models to predict CO₂, CO, NOₓ, and hydrocarbon emissions based on geometric and traffic parameters under Ugandan conditions. Vehicle movements were tracked with a high-precision device, and emissions measured directly from tailpipes using a calibrated exhaust gas analyser. Results show that road geometry and dynamic variables significantly affect emissions. In rolling terrain, vehicle speed and higher-order speed terms dominated, producing a Ushaped speed–emissions relationship, particularly for smaller petrol vehicles. In mountainous terrain, gradients, curvature, and interactions between speed, gradient, and curvature were more influential, amplifying emissions and nonlinear effects. Petrol vehicles were more responsive to geometric variations than diesel vehicles. CO₂ and CO models achieved moderate to strong predictive power (adjusted R² up to 0.918), while NOₓ and hydrocarbon models were less predictive. The study concludes that highway geometry, vehicle characteristics, and driver behavior strongly influence emissions, with small-engine vehicles producing disproportionately higher levels. Key gaps in the Uganda Geometric Design Manual were identified, including missing emission-sensitive parameters, environmentally optimal speed ranges, and fleet heterogeneity considerations. Recommendations include integrating environmental criteria into road standards, promoting sustainable transport, and enforcing emission regulations.