http://ir.haramaya.edu.et//hru/handle/123456789/81 Mon, 06 Apr 2026 09:42:22 GMT 2026-04-06T09:42:22Z http://ir.haramaya.edu.et//hru/handle/123456789/8122 MULTI-OBJECTIVE OPTIMIZATION OF MACHINING PARAMETERS OF MILD STEEL AISI 1018 UNDER DRY AND COMPRESSED AIR-ASSISTED MACHINING FREE ZIYAD; Dr. Dadapeer Bashir (PhD); Dr. Habtamu Alemayehu (PhD) In the machining process large amounts of heat are generated, and in order to remove them, it is necessary to utilize cutting fluids or adequate cooling agents, both of which are significant sources of waste production and detrimental to the environment. Due to these issues with cutting fluids, researchers were forced to develop novel methods, including dry machining, MQL, compressed air-assisted machining, and cryogenic machining. In this study, the key turning factors, such as cutting speed, feed rate, and tool overhang, were examined using the design of experiments to determine how they affected material removal rate and arithmetic average roughness (Ra) when turning AISI 1018 steel. Experiments were performed under dry cutting (DC) and compressed-air-assisted machining. Tests were designed according to Taguchi’s L9 orthogonal array. An ANOVA analysis was performed to determine the importance of machining parameters on the Ra and MRR using Minitab 18 software. Taguchi and an artificial neural network approach were used for output modeling. Finally, multi-objective optimization of the machining parameters was performed using Taguchi integrated with a genetic algorithm to minimize the surface roughness and maximize the material removal rate simultaneously using Mat lab R2019a. The findings showed that the material removal rate and roughness are significantly impacted by the cutting speed, followed by feed and tool overhang for dry and compressed air-assisted machining, respectively. Additionally, Taguchi models and artificial neural networks show strong correlations with experimental data. But artificial neural network models show more accuracy. The optimum machining parameters for multi-objective optimization during dry machining is Vc= 95.935 m/min, F = 0.104 mm/rev, and TOH = 40.024 mm, and the optimum result is MRR = 33.592 mm3 /sec and Ra = 1.443µm. Also, the optimum machining parameters during air assisted machining is Vc = 93.555 m/min, F = 0.1 mm/rev, and TOH = 41.701 mm, and the optimum result is MRR = 32.623 mm3 /sec, Ra = 0.468 µm. 100 Fri, 01 Mar 2024 00:00:00 GMT http://ir.haramaya.edu.et//hru/handle/123456789/8122 2024-03-01T00:00:00Z http://ir.haramaya.edu.et//hru/handle/123456789/7074 POWER QUALITY DISTURBANCE DETECTION, CLASSIFICATION AND MITIGATION USING WAVELET-NEURAL NETWORK: CASE OF DIRE DAWA ELECTRIC POWER DISTRIBUTION NETWORK Muluhabt Dires; Girma Beka (PhD.); Mohammad Firoz Alam Khan (PhD.) Power quality has become a vital issue recently due to the expansion of electrical load consumption and the growth of sensitive device usage in power systems. To maintain power quality and to ensure its reliability, power quality disturbances must be detected and classified correctly and precisely. Electric power disturbance is going to be a day-to-day phenomenon in Ethiopia. Among different Ethiopia regions, Dire Dawa is one part that is facing such phenomena. Thus, a modern power quality disturbance detection, classification and mitigation technique for Ethiopia in Dire Dawa electric power distribution network is necessary. Specifically, in this study wavelet-neural network is deployed to the Ethiopian context using collected data from Ethiopian Electric Utility. This technique includes feature extraction and detection, classification, and finally mitigation power quality disturbances. Eight signals, one normal signal, and seven power quality disturbances such as voltage sag, swell, interruption, harmonics, sag with harmonics, swell with harmonics, and interruption with harmonics are included in the study. In feature extraction and detection stages, the voltage signal of these power quality disturbances is simulated and generated and then changed into relevant data using wavelet transform. The feature extraction is carried out with energy features, approximation, and detail coefficients to reduce the dimensions of input data. In the classification stage, extracted features obtained from approximation and detail coefficients waveforms, serve as input data for training and testing of the classification stage. 578 samples with 14 features of eight signal classes are used as input to the classifier. The wavelet-neural network results show that the algorithm has high performance with minimum and overall accuracies of 98% and 99.32%. The classifier models like medium tree, coarse tree, and bagged tree are used to plot confusion matrix showing the accuracy and performance of artificial neural network. Finally, Unified Power Quality Conditioner is used as a mitigating mechanism to remove voltage-related power quality problems and improve power quality. The unified power quality conditioner improved the power quality by balancing the load voltage to its nominal value when either of the disturbances such as voltage sag, swell, or interruption occurred in the system. 89 Wed, 01 Nov 2023 00:00:00 GMT http://ir.haramaya.edu.et//hru/handle/123456789/7074 2023-11-01T00:00:00Z http://ir.haramaya.edu.et//hru/handle/123456789/6902 AN ASSESSMENT OF HARAMAYA UNIVERSITY DISTRIBUTION SYSTEM RELIABILITY ABDULAZIZ ADEM; Dr. V. Ramesh Kumar; Wehib Abubeker Providing quality and reliable electricity to customers plays an important role in every country's economy, politics, and technology. In Ethiopia, delivering the reliable electric power to the customers is the role of Ethiopian Electric Utility. However, for Haramaya University, power interruptions are a serious problem. This thesis assesses the reliability of Haramaya University's (HU) power distribution system (DS) and suggests improvement techniques. In this thesis, analytical method was used to evaluate the reliability performance of the HU power distribution system. According to the findings, the existing Haramaya University distribution network has serious reliability issues, and the root causes of power outages are overload, tree contact, wind, aging of poles and equipment, cable failure, maintenance and operational practices. The one line diagram of Haramaya University's existing and future distribution systems was modeled without and with diesel generators, fuses, reclosers, and solar distributed generators using ETAP 19.0.1 software and simulated differently in six cases. The results showed that, the reliability indices of existing system are beyond the Ethiopian standards and among all the cases of reliability improvement, the values of reliability indices were significantly enhanced in case 2 (underground ring distribution network). The System Average Interruption Frequency Index (SAIFI) was reduced from 196.38 to 1.1802 interruptions per customer per year; the System Average Interruption Duration Index (SAIDI) was reduced from 277.78 to 20.77 hours per customer per year; and the Average Service Availability Index (ASAI) increased from 96.83% to 99.76%. Because of power interruptions in Haramaya University's existing distribution system for the last two years, the estimated revenue loss of Ethiopian Electric Utility (EEU) was around 2,585,743.99ETB/year and HU lost between 1,688,046.05 to 5,961837.61 ETB/year. In case 2 the utility can save revenue of 2,239,549.9ETB/year and HU can save 5,762,746.38ETB/year. The installation of fuses and reclosers in distribution lines, the integration of solar distributed generators, and the conversion of an overhead radial network to an underground ring network can all improve distribution system reliability. Replacing old equipment and tree trimming will be an alternative solution for reliability improvement of the existing distribution system until the underground ring distribution system is completed. 115 Mon, 01 Aug 2022 00:00:00 GMT http://ir.haramaya.edu.et//hru/handle/123456789/6902 2022-08-01T00:00:00Z http://ir.haramaya.edu.et//hru/handle/123456789/6899 PERFORMANCE ANALYSIS OF SOFTWARE-DEFINED RADIO BASED RECONFIGURABLE ANTENNA ARRAY IN THE MILLIMETER WAVE WIRELESS COMMUNICATIONS Ahmed Abdella Seid; Mulugeta Atlabachew (PhD) The SDR-based reconfigurable antenna array over multiple-frequency bands and radiation patterns is very important to wireless communication. SDR components are attached to RA by using the RF front-end. This is to help the antenna to change user demands and wireless environment requirements through different configurations. In this thesis, we designed an eight element reconfigurable rectangular microstrip antenna array for millimeter-wave wireless communication, which was suitable for SDR. This was achieved by using a microstrip feed connection. The design considered the combination of frequency and radiation pattern reconfigurable antenna to improve the gain and bandwidth of the antenna. The work was important to minimize the generated interference to nearby users. The operating frequency band was Ka-band, which was 34.5-36.5GHz. This frequency was used to improve communication efficiency and high-speed broadband access. The type of Pin diode designed between antenna elements was MACOM MAAM-011275-DIE. It was very important to switch the frequency and radiation pattern in ON and OFF conditions for reconfigured purposes. The dielectric material of RT Duroid Rogers5880 with a dielectric constant (εr) of 2.2, substrate height (h) of 0.254mm, and low loss tangent tan of 0.002 was used in this research. ANSYSHFSS electronics desktop software tool was used to design a reconfigurable antenna array and simulate reconfigurable frequency and radiation patterns. The simulated reconfigurable frequency based on the operating frequency was 35.2GHz, 36.2GHz in an ON state, and 34.6244GHz, 35.0022GHz, 35.4467GHz, 35.7667GHz, and 36.4556GHz in OFF states, with good return loss and VSWR. The radiation pattern was simulated with main lobe direction and main lobe magnitude in ON and OFF states. The simulated results were -10º with 5.0196dB and 0º with 4.8810dB, respectively. Good performance analysis was obtained based on gain, bandwidth efficiency, radiation power efficiency, and energy efficiency. For this antenna, the efficiency was 97.3% (ON) and 97.4% (OFF), and the high directivity was 9.71dB (ON) and 9.65dB (OFF). Based on these parameters, an eight-element reconfigurable rectangular microstrip antenna array was presented. This is applicable for radar systems, 5G and beyond, satellite communications, wireless backhaul, research and development, point-to-point wireless links, wireless local area networks, and the Internet of Things (IoT). 98 Wed, 01 Nov 2023 00:00:00 GMT http://ir.haramaya.edu.et//hru/handle/123456789/6899 2023-11-01T00:00:00Z