AAU Institutional Repository (AAU-ETD)
Addis Ababa University Institutional repository is an open access repository that collects,preserves, and disseminates scholarly outputs of the university. AAU-ETD archives' collection of master's theses, doctoral dissertations and preprints showcase the wide range of academic research undertaken by AAU students over the course of the University's long history.
How to Submit Your Work
The repository contains scholarly work, both unpublished and published, by current or former AAU faculty, staff, and students, including Works by AAU students as part of their masters, doctoral, or post-doctoral research
- All AAU faculty, staff, and students are invited to submit their work to the repository. Please contact the library at your college.
You may contact digirep@aau.edu.et.with any questions about the repository
Colleges,Institutes in AAU-ETD
Select a college,institute to browse its collections.
Recent Submissions
Media Campaign Strategies for Awareness Creation: Focus on Some Organizations Working on Road Safety in Ethiopia
(Addis Ababa University, 2024-05) Yamrot Nigussie; Abdulaziz Dino (PhD)
The study aimed to investigate media campaign strategies for awareness creation: at Federal Transport Authority (FTA), Traffic Management Agency (TMA) and Bloomberg Philanthropies Initiative for Global Road Safety (BIGRS) organizations working on Road Safety in Ethiopia, thus, examine the awareness creation activities, identify media utilization performance, describe strategic media campaign practice & identify the challenges in strategic mass media campaign practices of the three. . The study employed descriptive research design and mixed research approach along with primary source of data and questionnaire and key informant interview as data collection instruments. These data were analyzed using descriptive statistics which is significantly supported by evidence in the form of tables, frequency and narrative forms. The total of 60 employees from the study organizations were participated using census method. The findings of the study reveals, road traffic crash conditions in Ethiopia require change, but, there is no use of adequate road safety awareness creation activities. The study also has found that face to face, mass media, internet & social media are used by all three organizations with varying degrees. In a view of print media, however TMA has a good trend of practical use that reach a specific target. The study has found that BIGRS have the strongest overall media campaign strategy compared to FTA and TMA. The study also assured that, the strategic media campaign practices were the use of data to design media campaign. However, budget constraint, lack of coordination and planning and knowledge of how to manage a successful media campaign were challenges of strategic mass media campaign in Ethiopia on the Road Safety. Thus, allocate sufficient budget for awareness-raising initiatives, provide capacity-building trainings, and conduct impact assessment on the respective media campaign programs & making the best and most accurate media selection were the forwarded recommendations by the researcher.
Roof Top Photovoltaic Energy Potential Mapping. Case Study of Jemo-1 Condominium Site; Addis Ababa, Ethiopia
(Addis Ababa University, 2024-07) Efrem Negussie; Tilahun Nigussie (PhD)
This study addresses energy potential mapping from photovoltaic panels on rooftops, focusing on geographic, physical, technical, and economic constraints for viable energy prediction. The research was conducted in Jemo condominium housing, representing typical living conditions. Geographic location potential, rooftop orientation for solar insolation, and technical potential aligned with energy demand scenarios were analyzed. Economic potential was also assessed. The adoption of solar PV systems in urban residential houses promises sustainable energy provision. This study evaluates solar energy feasibility through PV applications on rooftops, aiming for self-sufficiency in electrical energy, reduced carbon emissions, and alleviated energy scarcity. Secondary data were used to predict energy potentials via empirical formulations, spreadsheets, graphical analyses, and simulations. Optimal PV system performance was analyzed by incidence angle, azimuth classes, and roof slope. Google Earth was used to quantify physical potential by scanning rooftop orientations and directions. Technical potential was assessed by considering specific modules and their characteristics. Scenarios related to demand, supply, and backup were examined to predict optimums. Economic potential analysis concluded that a building block in Jemo-1 can pay 19,864.00 ETB per month for PV electric service. With a 143 m² rooftop area, 108 solar panels (1.31 m² each) and 7.2 kWhr additional power from storage equipment were determined. The capital investment for this setup is 1,462,406.40 ETB for a demand size of 14.26 kWhr/day or 5,205 kWhr annually. A 15-year life cycle and future worth assessment at local interest conditions suggest a capital investment of 805,649.00 ETB. A GHG effect analysis showed an annual emission of 1,077 kg CO2 from the conventional grid and 1,540 kg CO2 from the PV system, a 42% increase for the PV system.
Numerical Simulation and Performance Investigation of Bubble Pump Refrigerator
(Addis Abab University, 2023-10) Henok Habte; Solomon Teklemariam (PhD)
Approximately 30% of the primary energy consumed worldwide is used for refrigeration. In light of the global search for sustainable energy sources and energy-efficient methods of operation, solar-powered bubble pump refrigeration systems have gained traction as an alternative means of satisfying cooling requirements. Diffusion absorption refrigerators, sometimes referred to as bubble pump refrigerators, are driven by low-grade energy sources such as solar, waste heat, and recovery heat and do not require any mechanical moving components. However, in comparison to other cooling options, this system's coefficient of performance (COP) has been low. To increase the system's efficiency, more research on the effects of various parameters is required. The objective of this study is to enhance understanding of the behavior of the system through an examination of the impact of several critical factors. Using the programs ASPEN PLUS and EES, a thorough numerical simulation was conducted after a thermodynamic and system model was created. Every simulation was run with a standard total pressure of 25 bars. The model was used to forecast how different factors, such as generator heat, concentration of the refrigerant in a rich solution, and refrigerant purity, would affect the system's performance. The significant impact of refrigerant purity at the rectifier's outlet on coefficient of performance (COP) was one of the key finding. It was discovered that the COP rose from 0.15 to 0.36 as the purity improved from 0.950 to 0.999. It was also noted that a generator temperature of 200oC at 240W of thermal input was optimal at 25 bars of total system pressure. Additional heat rises did not appear to have a noticeable impact on the performance of the system. The one thing that makes this research stand out is the study of the effect of hydrogen on the COP of the system. It was observed that both heat absorbed at the evaporator (Qevap) and COP increased steadily and with similar degree of increments as hydrogen mass fraction increased from 0.5 to 0.95. This is due to the higher reduction of the partial of the refrigerant at evaporator inlet causing the refrigerant to lower its temperature further. Generally speaking, with more research done, the bubble pump refrigeration holds a lot of potential to take the place of traditional cooling technologies.
Silica Extraction from Aluminum Sulfate Byproduct and its Application as Rubber Filler in the Tire Industry
(Addis Ababa University, 2024-06) Tujuba Tamiru; Sintayehu Nibret (PhD)
Valorization of byproducts from chemical manufacturing is critical for reducing environmental impact advocating circular economy. High silica filter cake from Awash Melkasa Chemical Factory (AMCF) is disposed in landfills after producing aluminum sulfate. This study aimed to produce amorphous precipitated silica from byproduct of Awash Melkasa Chemical Factory and explore its potential as rubber filler in tire industry. Filter cake byproduct from Awash Melkassa Chemical factory was calcinated at a controlled temperature of 550 ℃ for 3 hours, followed by the extraction of amorphous silica using sol-gel technique. To characterize phase composition, chemical structure, morphology, and surface area of the as prepared silica filler, XRD, FTIR, SEM, BET, AAS, and XRF were employed. Silica with purity of 92.50% was obtained and tested as reinforcing rubber filler in tire industry. Curing characteristics of natural rubber compound filled with filter cake silica and commercial silica were examined with Rheo-line moving die and Mooney viscometer. Compound reinforced with filter cake silica has shorter curing time than compound filled with commercial silica due to finer particle size and high surface area revealed by SEM and BET respectively. Filter cake silica filled rubber compound showed better mechanical properties, compared to commercial silica reinforced rubber compounds. The lower Mooney viscosity of filter cake reinforced rubber compound makes filter cake reinforced rubber compound easier to process compared to commercial silica reinforced compounds. Morphology analysis of filter cake silica shows it is fine, and better filler for rubber applications in tire industries. Commercial silica has lower specific gravity and has less reinforcing ability in rubber compound, while filter cake silica filler has higher specific gravity that makes better reinforcing filler in rubber compounds. Therefore, amorphous silica from filter cake is potential filler in tire industry and the use of filter cake silica filler is a potential solid waste management in Awash Melkasa Chemical Factory and related industries.
Quality of Experience Modeling for Fixed Broadband Internet Using Machine Learning Algorithms
(Addis Ababa University, 2024-04) Abayneh Mekonnen; Dereje Hailemariam (PhD)
As the demand for dependable fixed broadband internet services continues
to grow, ensuring an excellent Quality of Experience (QoE) for end-users is
essential. This thesis centers on QoE modeling, employing advanced machine
learning techniques, specifically Support Vector Machine (SVM) and
Random Forest algorithms. The study utilizes subjective assessments and
Quality of Service (QoS) metrics, including latency, upload speed, download
speed, uptime, packet loss, and jitter, to comprehensively comprehend and
model the factors influencing user satisfaction.
The research incorporates an exhaustive feature selector to extract pertinent
features from the dataset, enhancing the precision of the models. Hyperparameter
optimization is carried out through a Grid Search approach to
fine-tune the models for optimal performance. To assess the models, a robust
cross-validation methodology is implemented.
The results indicate that SVM surpasses Random Forest in QoE modeling
for Virtual Internet Service Providers (vISPs) like Websprix and ZERGAW
Cloud with average accuracy score of 92% and 70% respectively. Conversely,
Random Forest proves to be the more suitable model for predicting QoE in
the case of the national ISP, ethio telecom with average accuracy value of
88%. This comparative performance analysis offers valuable insights into the
distinct strengths of each model for different service providers.
The research findings also indicate that employing both subjective and QoS
metrics in combination to model the user QoE yields superior model performance
and predictive outcomes compared to relying solely on subjective
assessments and QoS metrics.
These findings contribute to the ongoing discussion on QoE enhancement
in fixed broadband internet services, providing practical recommendations
for service providers based on observed model performances. The application
of machine learning, feature selection, and hyperparameter optimization
techniques underscores the importance of these methodologies in customizing
QoE models to specific service contexts, ultimately enhancing user satisfaction
in diverse fixed broadband Internet environments.