Ethiopia Institute of Technology- Mekelle

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Assessing the Impact of Improper Sidewalks on Pedestrian Safety and Level of Service in Mekelle City
(Mekelle University, 2025-07-22) Kibrom Weldu
Pedestrian safety is a vital yet often neglected aspect of urban development in rapidly growing cities like Mekelle, Ethiopia. This study examines how improper sidewalk conditions, such as narrow, obstructed, and poorly maintained paths affect pedestrian safety and the Pedestrian Level of Service. A mixed-methods approach was used to comprehensively assess pedestrian conditions in Mekelle City. Quantitative data collection involved measuring sidewalk widths, counting pedestrians, and conducting structured surveys to evaluate safety, usability, and infrastructure quality. Physical assessments also identified common obstructions like vendors, utility poles, and parked vehicles. PLOS was evaluated using the Highway Capacity Manual, considering factors such as surface condition, lighting, and crossing points. Complementing this, qualitative data were gathered through field observations and open-ended survey responses to capture pedestrian experiences, perceptions of safety, and challenges such as poor lighting, unmarked crossings, and obstructed walkways, especially during nighttime travel. The findings show that most sidewalks are narrower than the recommended 1.2 meters and often obstructed by vendors, poles, or construction materials, making them unsafe. PLOS ratings ranged from C to E, indicating poor walking conditions. Over half of respondents felt unsafe, mainly due to poor lighting, inadequate crossings, and lack of maintenance. This study concludes that Mekelle's pedestrian infrastructure significantly hinders walkability and compromises safety. Recommendations include adopting international design standards, enforcing clear regulations to prevent sidewalk encroachment, and incorporating inclusive urban design principles in future planning. These insights provide essential guidance for urban planners and policymakers aiming to create safer, more accessible pedestrian environments in Mekelle and similar urban contexts.
COMPARATIVE PERFORMANCE ANALYSIS OF LQR, PID, FUZZYPSO AND PSO-PID CONTROLLERS ON QUARTER CAR ACTIVE SUSPENSION SYSTEM
(Mekelle University, 2025-04-05) KOKEB GEBREMEDHIN
The purpose of this study is to evaluate and compare the effectiveness of various control strategies for active suspension. MATLAB/SIMULINK software is used for both the controller design and the quarter vehicle model. The control strategies PID, LQR, PSO-PID, and FUZZY-PSO are employed. The suspension travel response and sprung mass acceleration response two critical parameters for ride comfort and road handling are chosen, examined, and compared between the responses of the active suspension system and the passive suspension system in order to assess the effectiveness of the vehicle's suspension system. The two Key Performance Indicators (𝐾𝑃𝐼𝑀𝐴𝑋 𝑎𝑛𝑑 𝐾𝑃𝐼𝑀𝐴𝑋) are chosen to demonstrate a decrease in peak overshoot and a decrease in oscillation for the parameters chosen for the active and passive suspension system comparison. From this research, in summary, the PSO-PID and FUZZY-PSO controllers that were created exhibit exceptional performance in enhancing ride quality, hence increasing passenger safety and vehicle handling in the presence of two bumpy road disturbances. When it comes to decreasing to sprung mass acceleration and suspension travel, the PSO-tuned fuzzy logic controller performs the best, followed by PSO-PID, LQR, and PID controllers.
Design and Analysis of Solar water pumping system for Agricultural Farming of Sweet Potato
(Mekelle University, 2025-04-07) Tsegabrhan Gebretsadkan
Quality of life, sustainable development, and economic progress are all largely influenced by energy. The shift to renewable energy sources has become essential in light of the growing global energy crisis, which is characterized by rising demands and the depletion of fossil fuel resources. Solar energy is one of the most promising of these, especially when it comes to solving important issues with agricultural methods.The design and study of a solar photovoltaic (PV) irrigation pumping system for sweet potato growing in the Abraha-Atsbeha hamlet are the focus of this thesis. Because they rely on expensive and environmentally damaging diesel pumping equipment, local farmers today confront many challenges. To address these challenges, the research begins with a comprehensive review of existing literature on solar irrigation technology, identifying key gaps and challenges in the field. Building on this foundation, a conceptual design for the PV irrigation system is developed, incorporating essential components such as the PV array, pump, storage tank, and control systems tailored to the specific needs of sweet potato cultivation. A detailed computer model of the proposed system is created and simulated using advanced software tools, including CROWAT, MATLAB, PSIM, HOMER, PVSyst, EasyEDA, and Drawing.io. Benchmarking exercises are conducted to evaluate the system's efficiency across varying climatic conditions by adjusting parameters like temperature and solar irradiance. The findings highlight the effectiveness of the Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) algorithm in optimizing power output and ensuring efficient operation. According to the results, the Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) algorithm is a good way to maximize power output and operational efficiency. In summary, a comparative study shows that the solar-powered irrigation system has several benefits over conventional diesel systems, such as decreased carbon emissions and operating expenses. The potential of solar technology to revolutionize farming methods, enhance food security, and support a sustainable energy emphasized by is this study
Design and Optimization of a Hybrid Polyester Composite for Bus Roof Plates Using Jute and Reused PET Fiber Reinforcement
(Mekelle University, 2025-05-19) Natnael Abera
The automotive sector faces rising fuel consumption and pollution due to the increasing vehicle numbers. To mitigate these challenges, lightweight materials have become imperative to diminish the weight of automotive components. Additionally, addressing the pervasive issue of plastic pollution necessitates innovative solutions, such as recycling or reusing the primary plastic pollutant, polyethylene terephthalate (PET). This study tackles two interconnected issues: reducing vehicular weight through material substitution and mitigating plastic waste by reusing PET from discarded water bottles. The main objective of this study is to design and optimise a hybrid polyester composite material for bus roof plates for the modified ISUZU NPR71 4570cc, utilizing jute and reused PET fibers as reinforcement. Samples were prepared using the hand lay-up method, with fiber-to-matrix weight fractions ranging from 40% to 60%. Five laminates were created, incorporating alkali-treated jute fibers to enhance interfacial adhesion. Through a series of experimental tests, the tensile, compressive, flexural, impact strengths, density, and water absorption rates were conducted. The TOPSIS method was applied to assess and evaluate the properties of prepared laminate samples. Results indicate that the P-J-J-P orientation of NaOH treated jute fiber stands out as the optimal choice. The NaOH-treated jute fiber reduces water absorption by 47% (1.13% compared to 2.13% for untreated jute). A hybrid composite with a PJ-J-P layup and a 0°-90°-0° orientation was used to design a bus roof plate, optimised using Hyper Works-Optistruct and validated through re-analysis with ABAQUS. The optimised jute/PET hybrid polyester composite roof plate achieved a 34.58% weight reduction compared to a mild steel plate, decreasing from 210.38 kg to 137.63 kg, and saved 0.2765 litres of fuel per 100 km. This demonstrates that jute/PET hybrid polyester composites can effectively replace steel structures, offering significant environmental benefits and fuel savings without compromising performance or vehicle load capacity.
Design and Optimization of Bamboo/Glass Fiber Reinforced Epoxy Composites for Sustainable Wall Panel Application
(Mekelle University, 2024-11-12) Tedros Tilahun
Estimating the angle of arrival (AoA) of a coming signal can accomplished using various methods. In most cases algorithms are used for such purposes. However, algorithms are naturally complicated and expensive, and also cause a degradation in system performance. Therefore, other methods such as, 1800-hybrid rat race (HRR) coupler can be applied for effectively estimating the AOA of a coming signal. In this thesis work, an 1800 HRR coupler integrated with a 2x1 closely-spaced patch antenna array and a negative permeability metamaterial was studied for estimating AoA of a coming signal. The 1800 HRR was made up of a ring metallic sheet integrated with four additional branches placed at the edges of it. It operates at 10 GHz so as to make compatible with the 2x1 patch antenna array’s operating frequency. The simulation results show, the 1800 HRR coupler is characterized by 00- phase at the sum (Σ)-port while 1800 phase shift at the difference (Δ) port at the given operating frequency. In order to integrate with the 1800 HRR, a 2x1 array patch antenna with an inter - element distance of 0.6λ (where λ is the operating wave length) was designed. The antenna array workes at 10GHz with a maximum simulated gain of 8.824 dB while keeping the mutual coupling to a minimum of -23 dB. To further achieving miniaturization, the inter-element distance reduced to 0.4λ. The simulation result shows a resonance at 10 GHz frequency and maximum gain of 7.8 dB while the mutual coupling increased to -9 dB. The 2x1 patch antenna array with inter - element distance of 0.6λ -1800 HRR coupler system was able to estimate the AoA of the received signal from 00 to 190 with error of less than 50. While with a reduced inter – element distance to 0.4λ, the system was able to estimate signals from 00 to 500 with error of less than 50. Upon integrating split ring resonator (SRR) met materials, mutual coupling reduced to -15.6 dB without affecting the AOA of the system. This study was able to estimate AOA in a wide range of an incoming signal while keeping the inter – element distance smaller. The proposed design can be applied in radar system applications where accurate estimation of AOA of an incoming signal is needed such as in target tracking, surveillance, and navigation missions.
Design and Optimization of Bamboo/Glass Fiber Reinforced Epoxy Composites for Sustainable Wall Panel Application
(Mekelle University, 2025-05-19) Amelewerk Halefom
The increasing demand for sustainable construction materials has driven interest in natural fiber reinforced composites as eco-friendly alternatives to conventional materials. This study focuses on the design and optimization of bamboo/glass fiber-reinforced epoxy composites for application in sustainable wall panels, aiming to achieve a balance between mechanical performances, weight reduction, improve water resistance and sustainability. Different stacking sequences (B-G-B, G-B-G, G-G-B, and B-B-B) of bamboo and glass fibers were fabricated using the hand lay-up technique, preparation of 40% fiber and 60% of epoxy matrix incorporating alkali-treated bamboo fibers to improve interfacial bonding. The mechanical and physical properties of the fabricated composites were experimentally determined according to ASTM standards. A multi-criteria decision-making approach, using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), was employed to identify the optimal composite configuration. And it tells that G-B-G, characterized by a stacking sequence comprising 30% Bamboo, 10% glass, 60% epoxy, stands out as the optimal choice. The structural behavior of the optimized wall panel design was analyzed using Classical Lamination Theory. The optimization process, incorporating a genetic algorithm in MATLAB, aimed to minimizing weight and the constraint function is Tsai-Wu failure criterion. It results weight of the composite is 23.04kg, which reduced weight of the plywood weight by 15%, gypsum board by 5.8% and concrete panel by 38.4% and brick by 36%. Using literature review optimization, the water absorption of composite is 2.98% which reduced water absorption of the plywood by 7.11% of the gypsum board dry well is 9.11%, and concrete panel 2.11%, brick panel reduce by 8%. The optimized results were validated using ABAQUS of FEA. The maximum stress obtained from Genetic algorithm is 4.466Mpa and the maximum Von Mises stress is 8.511Mpa. The maximum deformation of the composite laminate is 12.2mm. This is less than the ultimate strength, proving the composite wall panel is safe and shows the safety factor is 2.5 against failure. The results of this study contribute to the development of sustainable and high performance wall panels using locally available bamboo resources.
DESIGN AND SIMULATION OF SINGLE AXIS SOLAR TRACKER FOR IMPROVING THE EFCIENCY OF PARABOLIC CONCNTRATOR
(Mekelle University, 2025-04-07) Awet Welay Hadgu
This research explores the design, simulation, and analysis of an active single-axis solar tracking system aimed at addressing the challenges associated with optimizing the performance of parabolic solar concentrators. Solar concentrators, particularly parabolic designs, offer significant advantages in harnessing solar energy for thermal applications, yet their efficiency is highly dependent on precise solar tracking. The current study develops a robust system designed to improve tracking accuracy, withstand challenging environmental conditions, and enhance overall system performance. Finite Element Analysis (FEA) was employed to validate the system’s structural reliability under extreme wind speeds of up to 55 m/s, a critical factor for ensuring operational stability in windy regions like Ethiopia. Additionally, dynamic modeling and control system design were carried out using MATLAB/Simulink, where a PID controller was tuned for optimal tracking performance. Results from simulations showed that the system achieved a tracking accuracy of over 96%, with minimal errors even under disturbances. These findings underscore the importance of integrating advanced tracking mechanisms in renewable energy systems to maximize energy capture and utilization. By addressing key challenges identified in existing parabolic concentrators, this study contributes significantly to the body of knowledge on solar energy systems and presents a practical solution for enhancing their efficiency, particularly in resource-constrained settings like Ethiopia
Design of an Adaptive Neuro-Fuzzy Inference System Controller for Temperature and Concentration Control in a MIMO Continuous Stirred Tank Reactor (CSTR)
(Mekelle University, 2025-04-07) Ybrah Zemcheal
The Continuous Stirred Tank Reactor (CSTR) is a critical unit in chemical processing industries, where precise control of process variables is essential for optimal product quality and efficiency. Among the key variables, temperature and concentration are particularly important to regulate. However, chemical processes often exhibit nonlinear and multivariable behavior, making conventional controllers less effective in real-time operation (PID control in CSTR exhibits sluggish or oscillatory responses for feed concentration, slow response to variable water flow, Poor robustness for uncertain parameters (e.g., reaction rates, heat transfer coefficients), perform poorly due to cross-coupling effects, less nonlinearity handling due to reaction kinetics. Challenges such as dynamic process variations, reactant nonlinearities, fluctuating environmental conditions, and diverse disturbances further complicate control. Additionally, most industrial chemical processes are multi-input multi-output (MIMO) systems, necessitating advanced control strategies and decoupling techniques. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed as an advanced control approach to enhance system performance and accuracy compared to conventional controllers. ANFIS integrates the structured knowledge representation of fuzzy logic with the adaptive learning capabilities of neural networks, offering improved control for complex systems. The performance of ANFIS is evaluated against a traditional PID controller through offline simulations using MATLAB/Simulink. The results demonstrate that ANFIS outperforms PID control in key performance metrics, including overshoot, rise time, settling time, and system stability. Furthermore, ANFIS exhibits superior disturbance rejection capabilities, making it a more robust solution for CSTR control in industrial applications.
Design of Fuzzy logic controller to series active variable geometry suspension system of automobile vehicle using full car model (With preview road profile information)
(Mekelle University, 2024-04-07) Binyam Tadros
Recent advancements in electro-mechanical active suspensions are presenting new opportunities, showcasing numerous benefits over traditional passive and semi-active systems, while also overcoming the significant drawbacks of other active solutions. This thesis introduces fuzzy logic controller with perfect preview information to improve the performance of Series Active Variable Geometry Suspension (SAVGS), which enhances conventional independent passive or semi-active suspensions by actively regulating the suspension geometry through an electromechanical actuator. The research work explores the benefits of this suspension type and provides an in-depth analysis of its simplest form. Additionally, it offers insights into the design process, including liberalized full-car modeling and selection. A control system designed to manage pitch and roll attitude of the chassis is also discussed. Simulation results demonstrate the viability of the proposed system as the fuzzy logic controller (FLC) is developed using MATLAB-Simulink for the SAVGS improves the suspension system, with various performance metrics (Passenger Ride Comfort, Suspension Safety, and Road Handling) evaluated at different speed for Road disturbance. The performance response at 20 kilometer per hour shows improvement in all the performance metrics, like in Passenger ride comfort is reduced in Vertical acceleration by 41.67% with reduced pitch and roll acceleration, Suspension safety is reduced in suspension deflection by 49.1% in front and 43.1% in rear sides with reduced velocity, and in road handling the tire deflection reduces by 46.3% at front and 36.9% at the rear sides of the car
DESIGN, DEVELOPMENT, AND EXPERIMENTAL INVESTIGATION OF A PORTABLE MULTI-BLOCK MAKING MACHINE
(Mekelle University, 2025-05-19) Kibrom Gidey
This thesis presents the design, development, and experimental investigation of a Portable MultiBlock Making Machine, aimed at overcoming the limitations of existing single-block and multiblock machines. The innovative design combines portability with high output efficiency and reduced energy consumption, making it suitable for small to medium-scale manufacturers in diverse construction environments. The developed prototype demonstrates the capability to produce five hollow cement blocks simultaneously, adhering to industry standards for block quality and structural integrity. Finite Element Analysis (FEA) was employed to validate the structural reliability and production efficiency of the machine. Key findings from the FEA indicate that stress distribution, displacement, and strain levels remain well within acceptable limits. The von Mises stress analysis confirms that all components experience stress values significantly below the yield strength of ASTM A36 mild steel, ensuring that the machine operates within the elastic deformation range, thereby preventing permanent failure. Additionally, the displacement analysis reveals minimal deformation across all structural components, indicating robust mechanical stability during operation. The strain analysis further validates effective stress distribution, demonstrating that material selection and design choices mitigate localized strain concentrations, enhancing overall durability. The Factor of Safety (FOS) analysis provides a minimum safety margin of 1.5, reinforcing the design's compliance with industrial safety standards and its ability to withstand operational loads. The successful fabrication and testing of the prototype confirm that the Portable Multi-Block Making Machine offers a high-output, energy-efficient alternative to conventional block-making methods, significantly improving productivity and lowering operational costs. Looking ahead, future enhancements should focus on fatigue analysis, structural reinforcement in high-stress areas, and optimization of mold alignment to further boost efficiency and lifespan. The integration of automated control systems and renewable energy sources could also enhance sustainability and operational flexibility.
DESIGN, MODELING AND SIMULATION OF ROBOTIC KRAR STRUMMER FOR ONE-HANDED INDIVIUALS
(Mekelle University, 2025-03-28) ABRAHALEY KAHASY BRHANE
Playing traditional musical instruments, such as the Krar, typically requires two hands, which limits accessibility for individuals with upper-limb disabilities. This thesis addresses this challenge by designing, modeling, and simulating a robotic Krar strummer to assist one-handed individuals in playing the Krar, a traditional string instrument from Ethiopia and Eritrea. Despite advances in assistive technology, few solutions exist for traditional instruments, leaving a gap in accessibility for one-handed musicians. A robotic manipulator was developed to replicate the strumming motion of a human hand, enabling users with one functional hand to engage with the instrument. A three-dimensional model of the robotic strummer mechanism was created using SolidWorks, and its dynamic behavior and control system were simulated in MATLAB/Simulink. Rhythmic trajectories based on traditional Krar performances were analyzed, and a PID controller was implemented to ensure precise strumming patterns. Key findings from the simulations show that the robotic strummer accurately replicates rhythmic patterns with minimal error. The system demonstrated high accuracy in following predefined trajectories, with errors well within acceptable limits set for RKS. Joint space trajectory errors were minimal, with Joint 1 showing a maximum deviation of 0.091 degrees and Joint 2 a maximum deviation of 1.56 degrees without disturbance. With disturbance present, Joint 1 showed a maximum deviation of 1.7 degrees and Joint 2 a maximum deviation of 3 degrees. The controller effectively maintained precise alignment with the desired trajectories, ensuring stable operation. The simulation results under disturbance also demonstrated the system's ability to maintain stability and accuracy, with errors considered insignificant in terms of the rhythmic pattern. This research contributes to enhancing accessibility, enabling one-handed individuals to participate in music creation, promoting inclusivity in musical expression. The detailed design, modeling, and simulation results confirm the feasibility of the proposed robotic Krar strummer system. This research represents a step forward in assistive technology, bridging the gap between traditional music instrument and accessibility for individuals with disabilities.
DEVELOP A Bi-DIRECTIONAL ENGLISH - NUER MACHINE TRANSLATION USING DEEP LEARNING APPROACH
(Mekelle University, 2024-12-28) Lemlem Gebremedhin
The advancement of deep learning has revolutionized natural language processing, with machine translation playing a pivotal role in bridging linguistic barriers. This research focuses on developing a bi-directional English-Nuer machine translation system using deep learning techniques. The primary challenge is the lack of linguistic resources for the Nuer language, hindering its technological representation and global accessibility. To address this, the study constructed a parallel corpus of 46,134 English-Nuer sentence pairs and employed models such as GRU, Bi-GRU, LSTM, LSTM with attention and transformer mechanisms. The findings revealed that the Transformer model achieved superior BLEU scores compared to the other architectures, scoring 0.2567 for Nuer-to-English and 0.2431 for English-to-Nuer translations. The results highlight the potential of the proposed deep learning-based machine translation for low-resource languages. As future work, the researcher highlights to explore integrating speech-to-text and textto-speech capabilities to enhance usability.
Developing Trip Production and Mode Choice Model for Home Based Trips: The Case of Hawelti Sub-City Residents, Mekelle - Ethiopia
(Mekelle University, 2020-03-25) Gerezgiher Gebrewahd Hagos
Hawelti sub City considered one of the most rapid increases in population and crowded subcity in Mekelle city. Hawelti sub-city does not have a transportation model; hence, developing a model is considered very important for predicting the average daily trips and use of each mode. The aim of this study is to develop trip production and mode choice model for home-based trips in Hawelti sub-city residents. The trip production includes a trip for work, education, shopping, social and recreation whereas the mode choice focuses on work and education trips. A household interview survey was used as a data source in addition to secondary data obtained from the municipality of Hawelti Sub-City. Trip production was analyzed using multiple linear regressions and multinomial logistic regression was utilized in the analyses of mode choice with statistical data processing software SPSS. The modes of transport considered in the model are Walking, Bajaj, Private car, Minibus Taxi, and Service (Company or school provided transport). Minibus taxi is found to dominate with 44% share followed by the company provided service with a 22.8% share for all trips. In the developed model the factors that affect the trip production are the number of students, employed persons, monthly income, the number of females and the age above 45 in the household. Moreover, the factors that significantly affect the choice of transport modes for employees were total travel time, work type and family size. The mode choice model developed for the case of students the significant factors were found to be travel time and gender. The developed models were significant at 95% confidence level and exhibits a good fit for the data with the coefficient of determination (R2 ) of 0.889 for the general trip production and the adjusted goodness of fit measure statistics rho square (ρ2) of 0.823 and 0.824 for the work and student models respectively for the whole study area. The models are validated to be capable of predicting 90.97% and 87.2% of the preference of trip makers for the work and education mode choice models respectively.
Effect of Filler Types (Crushed Stone, Gypsum and Lime Kiln-dust) on the Marshal Properties of Asphalt Concrete
(Mekelle University, 2020-05-18) FREWEINI WELU
Roads are one of the country’s basic infrastructural facilities, which needs a precise engineering design to minimize the life cycle cost by achieving reliable in-service performance. For the paved road types, pavement structure design and mix design of asphalt concrete mixture including adequate structure with proper drainage system and durable raw materials are the major considerations to attain reliable pavement performance that is adequately strong, durable and resistive to fatigue, and permanent deformation by considering economical aspect. The HMA contains coarse aggregate, fine aggregate and mineral filler coated with a bitumen binder and air and the mechanical properties of bituminous road pavement depend decisively upon the properties of its filler-bitumen. Although Mineral filler plays a major role in filling voids of the mixture and on the modification of the asphalt concrete properties like stiffness of the asphalt mortar matrix, improving the rutting resistance of pavements, it needs high intention on the content of the mineral filler since the excessive use have also weaken the properties of the mixture. In Ethiopia, crushed stone from dust extractor is conventional filler material in almost all flexible pavement construction projects but deficiency of this mineral filler happens and leads to crush aggregate for that purpose, which increase the production cost and environmental deterioration of the area. The main objective of this thesis is therefore to investigate the effect of the filler types (crushed stone, lime kiln-dust, and gypsum) on the marshal properties of asphalt concrete and to analyze the cost breakdown for the production of hot mix asphalt with these different filler types. To evaluate the effect of these selected filler types marshal mix design was used and conducted the laboratory test for marshal stability, flow, air void, voids in mineral aggregate and voids filled with bitumen by preparing a total of 90 specimens compacted by marshal compactor by 75 blows on the upper and lower sides of the mold. From the marshal laboratory test, asphalt concrete with crushed stone, gypsum and limekiln dust attains all the requirements specified on the ERA manual. Comparing the filler types, mixture with crushed stone filler attains the highest stability (9.45KN) at 2% filler content. For the asphalt concrete mixture at 3% filler content, mixture with gypsum filler attains the highest stability (9.4KN). From the cost break down analysis for the production of 1m3 HMA, lime kiln-dust and gypsum lowers the production cost by 1.34% and 1.21% respectively with the comparison of HMA with crushed stone filler.
Efficiency Improvement in MV Distribution System through Feeder Reconfiguration (Case Study: Adwa Distribution System)
(Mekelle University, 2025-04-07) Yosef Amaha
The electric power industry is increasingly challenged by rising load demand, aging infrastructure, and the complex spatial distribution of electrical loads, all of which undermine distribution system efficiency. These are especially pronounced in radial networks, where high technical losses and voltage deviations compromise power quality and reliability. Adwa feeder, a 15 kV radial distribution system in Ethiopia, embodies these concerns, with technical losses reaching 940.84 kW, voltage levels dropping to 0.83 per unit, and line loading peaking at 148.14 percent. This study explores feeder reconfiguration using Particle Swarm Optimization (PSO) to improve energy efficiency, voltage stability, and line overloading under varied load conditions. Load flow analysis was conducted using the Backward/Forward Sweep method in MATLAB under peak, medium, and minimum loading conditions, with total demands of 7,839 kW, 4,710 kW, and 2,160 kW, respectively. PSO identified an optimal switching scheme by opening sectionalizing switches 52 and 71, keeping tie switches 79 and 82 open, and closing 80 and 81. The optimized configuration reduced peak losses by 35.7%, lowering them to 604.87 kW and improving minimum bus voltage to 0.9161 per unit. For medium and minimum loads, losses dropped from 570 kW to 370 kW and from 140 kW to 90 kW, respectively, improvements of 35% and 36% with corresponding voltage profile enhancements. To validate robustness, Monte Carlo simulations (1,000 iterations, ±10% load variation, ±0.05 PF deviation) confirmed the optimized topology sustained losses near 605 kW and voltages above 0.9 per unit under uncertainty. Furthermore, upgrading the most overloaded segment (Line 1–2) to an AAC 150 conductor further improves losses to 524.32 kW. While this upgrade alone provided an 8.6% gain beyond reconfiguration, the combined effect achieved a total loss reduction of 44.3% from the original case. These results demonstrate that intelligent feeder reconfiguration, enhanced by PSO and supported by probabilistic analysis, provides a scalable, cost-effective solution for improving performance in radial distribution networks like Adwa's.
Enhanced Inception ResNet V2 Model for Grape Leaf Disease Detection and Classification
(Mekelle University, 2025-01-25) Efrem Gebrewahd Gebreslassie
Grapes are one of the most widely consumed and globally traded crops, benefiting both agricultural economy and healthy wise. However, their vulnerability to diseases can negatively affect the quality and quantity of the grapes being produced. The most common way of detecting and classifying these disease is through the use of human experts (manual inspection method), such as pathologists and botanists. This manual inspection method is prone to error, time consuming and inefficient for large scale farms. To tackle this problem several researchers have built an automated system that detects and classifies plant diseases in a more accurate and faster way. While these studies show a reasonable result but still struggle with several issues, like poor accuracy, increased computational complexity and strong overfitting. Thus, our model addressed these issues by introducing an enhanced version of Pretrained Inception ResNet V2 architecture, By integrating a lightweight Reduction Module C which is responsible for reducing the grid size of the input image from 8 X 8 to 3 X 3 while increasing the feature maps from 1536 to 1600. This module allows the model to capture more complex features while ignoring relevant information leading to improved feature extraction capability. The proposed model achieved a superior F1 score of 99.89% on the validation set with only 0.21 million trainable parameters, outperforming EfficientNet-B4 (99.81% F1 score, 0.46 million parameters), Xception (99.73% F1 score, 1.05 million parameters), and the baseline Inception ResNet V2 (99.87% F1 score, 0.79 million parameters) in both accuracy and computational efficiency. The results show that the suggested model presents a promising solution for accurate and efficient grape leaf disease detection and classification.
Enhanced Solar Irradiation Forecasting Using LSTM
(Mekelle University, 2025-03-12) Silas Gebretsadik Mebrahtom
Accurate forecasting of solar irradiation is critical for improving grid stability, optimizing energy storage, and maximizing photovoltaic (PV) system efficiency. Traditional forecasting methods, including statistical and numerical weather prediction models, often struggle with the nonlinear and complex nature of solar irradiation data. This research work explores the application of deep learning techniques, specifically Long Short-Term Memory (LSTM) neural networks, to enhance day-ahead solar irradiation forecasting for solar energy applications. In this research, an LSTM-based model was developed and trained using historical irradiation data, covering the period from January 1984 to March 2025 in Mekelle. The methodology involved data collection, cleaning, and preprocessing, followed by model training and evaluation. Key preprocessing steps included removing anomalies and normalizing the data set using Min-Max scaling. The LSTM model demonstrated superior performance compared to traditional machine learning models, with a Mean Bias Error (MBE) of 0 kWh/m²/day, Mean Absolute Error (MAE) of 0.46 kWh/m²/day, and Root Mean Squared Error (RMSE) of 0.65 kWh/m²/day. The model demonstrated a 71% lower RMSE in winter compared to summer and achieved 56% higher accuracy on sunny days than on cloudy days. These improvements can be attributed to the more stable weather conditions of the winter season and the consistency of solar irradiation on sunny days in Mekelle. The model was evaluated using two different dataset sizes, 5556 and 15040 data points. With the larger dataset, performance improved by 15%, highlighting the critical role of data availability in enhancing model accuracy and reliability. The results suggest the potential of LSTM networks in providing reliable day-ahead solar irradiation forecasts, contributing to the broader adoption of renewable energy. This study recommends integrating the solar irradiation forecasting model with energy forecasting systems to optimize grid performance and storage utilization. Future research should explore extended datasets, additional meteorological parameters, and ensemble methods to enhance the adaptability and accuracy of LSTM-based forecasting models
Estimating Traffic Congestion Costs for selected Road of Mekelle City
(Mekelle University, 2020-06-28) Wahd Solomun
Traffic congestion is a problem which occurs on road network characterized by slower speed, longer trip time due to excessive vehicles from different direction. Traffic congestion have a negative impact on society such as late reach to work place by increasing travel time, on health by creating stress, mentality and physical discomfort, increasing fuel consumption and air pollution. Mekelle is one of the fastest growing city in Ethiopia. Accordingly, traffic congestion is growing extremely in the city and results time wastage on travel and other direct and indirect effects on the society. This study is concentrated on two selected intersection the first one is four leg signalized intersection which is found around commercial bank of Ethiopia, main branch and the second one is four leg intersection which is found around Relief Society of Tigray in this intersection traffic light is not functional for about two years but after data collection performed the traffic signal was maintained and the intersection become signalized. Then again traffic volume data was conducted at signalized case. The main objective of this study is to estimate traffic congestion costs for selected intersection of Mekelle city and to suggest the possible counter measure for the problem. Primary and secondary data was collected to accomplish the study objectives. Primary data traffic volume, vehicle occupancy, signal timing, geometric data and daily labor cost was collected. The traffic volume count was made using video recording starting in the morning peak time 7:00AM-10:00AM, at noon time 11:00 AM-2:30 PM and the evening peak time 4:30 PM- 7:30 PM at 15 minutes interval was done for both intersections. The vehicles were counted by type passenger car, bus and small and medium truck vehicles. The average vehicle occupancy was collected based on traffic engineering vehicle occupancy data collection manual. After the data was collected data analysis was made. Delay at the intersection was analyzed using SYNCHRO software. Then using the collected data and delay annual peak hour cost of traffic congestion in both intersection was estimated. The cost of congestion consists travel time cost, fuel consumption cost and cost of co2 emission gas due to excess fuel usage. The result is found about (5,339,609.37ETB annual peak hour cost) at CBE four leg signalized intersection, (3,789,746.99ETB annual peak hour cost) at REST four leg unsignalized intersection, and (3,181,684.41ETB annual peak hour cost) at REST four leg signalized intersection. Annual peak hour travel time cost represents the opportunity costs of wasted time on congested intersection which shows the largest category at CBE intersection found about 4,311,552.5ETB nearly 81% of total cost of the intersection, at REST unsignalized is about 3,116,165ETB about 82% of cost of intersection and REST signalized have 2,618,690.9ETB about 82% of total intersection cost. Meanwhile annual peak hour cost of fuel is the second contributor to the overall cost of congestion with 1,009,870.3ETB at CBE, 661,988.9 ETB at REST unsignalized intersection and 552,987.4 ETB at REST signalized intersection which is about 18% of the total cost. On the other hand annual peak hour emissions costs is the least contributor to the overall cost of congestion and estimated about 18,186.57ETB at CBE intersection, about 11,611.09ETB at REST unsignalized intersection and 10,006.11 ETB at REST signalized intersection. The cost of congestion result shows the effect of congestion is highly concentrated on the travel time of public transport users’ means 78% of the travel time cost is for the public transport users.
Evaluation of irrigation water allocation for improving water use efficiency and conflict resolution in Hatset irrigation scheme, Eastern Tigray, North Ethiopia
(Mekelle University, 2025-03-25) Lema Kiros Lema
Efficient water allocation is crucial for enhancing irrigation water use efficiency and mitigating conflicts among users, especially regions where water is limited. This study tried to evaluate the irrigation water allocation system to optimize water allocation and improve conflict resolution mechanisms in the Hatset irrigation scheme, Eastern Tigray, North Ethiopia. The primary data was collected through soil sampling, flow measurements, household surveys, key informant interviews, and focus group discussions, and the secondary data was collected through meteorological, hydrological and spatial data. WEAP model used to assess current water allocation scenarios and propose improved strategies. Additionally, CROPWAT model was used to estimate crop water demand and HEC-HMS also used to estimate reservoir inflows. The findings reveal, unmet demand 0 m³, 0 m³, 895,360 m³ and water losses 155,721 m³, 309,160 m³, and 430,479 m³, head, middle and tail-end users respectively. Three scenarios were analyzed: a reference scenario, an improved water use efficiency scenario, and an irrigation expansion scenario. The reference scenario was business-as-usual approach and the enhanced water uses efficiency scenario demonstrated a 37.5% reduction in water demand by incorporating canal lining, efficient scheduling, and efficient irrigation techniques and the irrigation expansion scenario, which increased the irrigated area but resulted in a 23% increase in water demand with no unmet demand. Moreover, the study investigated the effect of efficient water allocation in resolving conflicts within the Hatset irrigation scheme, where infrastructure issues and governance gaps created significant disparities. It conducted how inadequate access for tail-end users caused conflict, while traditional and formal mechanisms proved ineffective due to poor coordination. The proposed hybrid approach, which integrated community driven and IWUAs, addressed systemic challenges and promoted sustainable conflict resolution.
EVALUATION OF SUSTAINABLE URBAN MOBILITY IN THE CITY OF MEK’ELE
(Mekelle University, 2020-06-28) Yoseph Solomon
Currently, cities are looking for all round transport sustainability. Nevertheless, urban transportation can create a problem on economic, social and environmental aspect of the city. Up on observation residents have complaint on the fare for local transportation, vehicles noise disturbance and services provided by public transport. This thesis indexed eleven urban sustainable transport indicators. Based on the indexed results of the tool, SWOT analysis is conducted. The study also sought to identify the remedial measures that should be undertaken to mitigate the problems. The study area is defined to be Mek’ele city. The sustainable urban mobility indicators are assessed through a procedure that requires various method of data collection and data processing. World Bank backed online software was used after data legitimizing and confirmation was made between Tigray Construction Road and Transport Bureau and the world councils of urban sustainable development headquarter at Geneva, Switzerland. The indicator, access to mobility service, is based on percentage of people living within a radius of 400 meters from a public transport stops. Fatalities were considered as the number of deaths per annum per 100,000 inhabitants. For mobility space usage, area of roads, open parking, service areas and petrol stations were considered. Length of road network with sidewalks, with bike lanes, in zone 30 (km/h) and total length of city road network were served as input for the indicator of opportunity for active mobility .The social aspects such as, access for mobility impaired groups, comfort and pleasure, commuting travel time and security is indexed using structured questionnaire as part of the tool. For noise hindrance, sound measurements were taken. Affordability of public transport for the poorest quartile is measured by GDP and population’s lowest quartile income as a data. The sustainability for Mek’le city transport system is 4.93/10, suggesting weak sustainable mobility conditions for the city‘s transport system. The SWOT analysis has the prospects of being used in policymaking, defining strategic directions and the implementation of measures towards the fulfilment of sustainable urban mobility in the city of Mek’ele.