Zede Journal of Ethiopian Engineers and Architects

EVALUATION OF PUBLIC BUS STOPS LOCATION AND SPACING (THE CASE OF SELECTED ROUTES OF ANBESSA CITY BUS SERVICE ENTERPRISE)

2024-08-05T08:48:47+00:00

Currently, the primary challenges in Addis Ababa include traffic accidents, comfort issues,
travel delays, and productivity problems for travelers. To address these issues, it is recommended to enhance public services by incorporating suitable geometric features,
particularly for bus stops. This study focused on evaluating existing bus stop locations and
spacing and put remedial measure for any existing drawbacks on public transport Road
networks particular on Anbessa City Bus Service Enterprise (ACBSE) routes. Observation, field measurement, GPS method tracking location of bus stops and GIS method produced point mapping were the methodologies used for the study. Travel speed, bus stop location, its configuration and service coverage radius data were acquired. The maximum travel speed that was determined during the study period was 26km/hr. Based on the analysis result, 29% of Mid-Block pullout bus stops should be changed to mid-block curb-side and mid-block bus bulb bus stops on street having vehicle parking. Generally, 8% of bus stop locations needs future modification. From the research finding, the final bus stops location and spacing depend on the combined effect of location with respect to the nearest
intersection, travel speed, service coverage radius, topographical limitation, safety issues
and passenger loading of the surrounding area.

RELIABILITY-BASED NUMERICAL MODELING FOR INVESTIGATION OF THE IMPACT OF PRINTING PARAMETERS ON BUILDABILITY OF 3D PRINTED CONCRETE STRUCTURES

2024-08-05T08:51:16+00:00

The significance of 3D concrete printing (3DCP) as an additive manufacturing technology has increased over the past few years. Both academic research studies and large-scale industrial realizations of 3DCP have shown that it represents a viable alternative to traditional concrete mold casting. The key reason for this rapid development is that urgent challenges of the construction sector, in particular sustainability and productivity, are addressed. However, previous studies on technological progress have mainly been experimentally driven. The introduction of appropriate numerical modeling techniques would, therefore, further foster the success of 3DCP by providing insight into the structural behavior, which is beyond experimental possibilities. The present study introduces a numerical modeling technique for the analysis of 3DCP wall structures using a time-dependent reliability analysis. Uncertainties occurring throughout the printing process and time dependent properties of printable concreteare considered. In addition, sensitivity analysis of random variables is done, which could be used as indicative preference for future process optimizations.The results yield valuable insight into the influence of printing process parameters on the failure of 3D printed concrete structures. The numerical model predicts build ability of a 3D printed concrete wall structure as it is in very good agreement with experimental results of similar studies.

THE PERFORMANCE OF PRIVATE RESIDENTIAL REAL ESTATE DEVELOPERS IN ETHIOPIA: THE CASE OF ADDIS ABABA

2024-08-05T08:52:31+00:00

The issue of providing adequate housing tothe general public is critical in both developed and developing nations. This requires continuous monitoring of performance in the provision of housing as a fundamental approach to enhance efficiency and establish a strategic framework for achieving better productivity. This study focuses on the performance evaluation of real estate firms in Addis Ababa and identifies the obstacles encountered that would influence their construction operations and management. The primary goal of this research is to introduce the concept of project performance, identify the factors influencing performance and propose strategies for enhancing performance in real estate firms. The qualitative research methodology employed involved non-random sampling. The methodology involved preliminary investigation and a pilot study, to refine and explore the research areas. Through the data analysis process; the study underscored the significance of focusing on customer satisfaction, cost overruns and other financial aspects when considering performance metrics. Furthermore, among the factors impacting performance; material price fluctuations, exchange rate variations and construction material shortages ranked highest in their order of appearance. The study's findings culminate in essential recommendations for improvement strategies. In conclusion, it emphasizes the necessity of a collaborative effort among all stakeholders to notably elevate the real estate sector.

PERFORMANCE ENHANCEMENT OF KALITY WASTEWATER TREATMENT PLANT’S UP FLOW ANAEROBIC SLUDGE BLANKET REACTOR USING SURFACE RESPONSE METHODS

2024-08-05T08:53:26+00:00

The main aim of this study was to examine and optimize the performance of anaerobic sludge blanket reactor (UASB) using the surface response method-central composite design (RSM-CCD). The influences of several operational parameters were considered, including temperature (0 to 30°C), organic loading rate (OLR) (1 to 3 kg COD/m3·d), pH (6.3 to 7.8), and hydraulic retention time (HRT) (4 to 12h). The pilotscale reactor had a volume of 48.8 L. The RSM-CCD was used for the determination of the number of runs and the optimization of operational parameters. According to the derived model, the reactor exhibited optimal results under the following conditions: Temperature (23.0°C), OLR (2.3 kg COD/m3·d), pH (7.5), and HRT (11.4h). Removals of 84.1%, 99.9%, and 100% for chemical oxygen demand (COD), total

COMPARATIVE ASSESSMENT OF THE EFFECTS OF PLANT BASED GUMS ON RHEOLOGICAL CHARACTERISTICS OF MAIZE DOUGH AND ITS BREAD QUALITY

2024-08-05T08:54:11+00:00

Bread made from maize is considered as gluten free and thus recommended for people living with celiac disease. However, bread made from maize has inferior quality when compared to bread made from wheat. The aim of this investigation was to explore how plant-based gums affect the rheological attributes of dough made from maize flour and the resulting bread quality. Various types of plant gums were use data ratio of 3% to the flour weight basis. Control samples were prepared using maize and wheat flours. To provide a basis for comparison, dough and bread samples made from wheat flour were also used. The study examined the farinographic, pasting,gaseous release and dough development characteristics. Proximate composition, loaf specific volumes, texture character, and sensory qualities of bread were also examined. The inclusion of gums in maize flour reduced the dough's water absorption capacity (WAC) and degree of softening(DS). Treatment with gums also had a considerable impact on most of the pasting profile. Furthermore, treatment with gums improved bread loaf weight and specific volumes. The firmness of the maize bread was higher than the maize bread prepared from the dough samples treated with gums.

EVALUATION AND ADJUSTMENT OF INFRASTRUCTURE LEAKAGE INDEX FOR TOWNS IN DEVELOPING COUNTRIES

2024-08-05T08:54:51+00:00

Evaluating water loss and the performance of urban water supply utilities is critical. The objective of this research was to evaluate the applicability of the Infrastructure Leakage Index (ILI) formula for towns of developing countries and suggest adjustment factors.Basic water supply data from nine towns of Ethiopia was used to calculate ILI and develop modification factors. Water supply development level factor was determined based on the actual water production and optimal consumption if there was sufficient supply. Asset management factor was developed considering the categorization of Ethiopian towns which was related to expected water supply level based on development level. The study showed the Unavoidable Annual Real Loss (UARL) formula gave similar values for any type of water supply system whether developed or not. Except for Addis Ababa, the calculated ILIs utilizing the standard formula were less than four indicating unrealistic very good performance. Applying the adjustment factors, realistic ILI values were obtained reflecting the realistic performance of water utilities in developing countries, requiring timely appropriate water loss reduction measures.

DEFORMATIONAL BEHAVIOR OF FIBER REINFORCED CEMENT BASED MATERIALS UNDER REPEATED LOADING

2024-08-05T08:51:54+00:00

Bond degradation of the constitutematerials of the structure causes an increase in residual deflection and total surface crack width which reduces overall performance of structures. Advanced construction materials such as ultra-high strength fiber-reinforced concrete,commonly known as engineered cementitious composite (ECC) and fiber reinforced strain-hardening cement-based composites (SHCC)are designed to offer superior mechanical properties with multiple fine cracks and deformability than conventional concrete materials because of the bridging effect of embedded fibers. In general, both ECC and SHCC can be suitable for applications involving repeated loadings. However, the performance depends on magnitude, type of loads, etc. In this study, deformational behavior of fiber reinforced cement-based materials, ECC and SHCC, under repeated loading (low cycle fatigue) is investigated. Test results showed that, ECC is bendable, the deformation can be easily detected and has high impact resistance. On the other hand, SHCC has the potential for multiple cracking and strain-hardening behavior. ECC and SHCC can thus be used for strengthening and retrofitting of structural lements in addition to their benefits for new construction works.

MACHINE LEARNING BASED CONTAMINATION DETECTION IN WATER DISTRIBUTION SYSTEM

2024-08-05T08:55:58+00:00

Water is a necessary component of all human activities. According to the United Nations World Water Assessment Program, every day, 2 million tons of sewage, manufacturing, and agricultural waste are discharged into the world's water. Due to population demands and dwindling clean water supplies as well as available water pollution management mechanisms; there is an urgent need to use computational methods to intelligently manage available water. This paper proposes artificial neural networks, specifically, Convolutional Neural Networks, for automated water impurity detection. To refine the model, the picture of turbid water in the pipe was used to detect events. The algorithm of deep learning achieved 96.3 percent accuracy after extensive training with a dataset of 4220 images reflecting various levels of contamination. This shows that, the model can be used in water system pollution detection.

CALIBRATING RASPBERRY PI V2.1 CAMERA AS AN ABSOLUTE LUMINANCE METER FOR SMART LUMINAIRE SYSTEM SENSING APPLICATIONS

2024-08-05T08:56:42+00:00

This article presents the conception and realization of a self-contained, absolute luminance level measurement device using a Raspberry Pi v2.1 camera system and single-board pocket size Raspberry Pi computer for a smart luminaire system sensing applications. The work presents Raspberry Pi v2.1 camera module footage in raw Bayer data formats, radiometric characterizations, raw Red, Green, Blue (RGB) to absolute luminance meter calibration and validation results. The developed absolute luminance meter is very simple, efficient, compact and suitable for absolute luminance level sensing measurement. Results obtained from the luminance meter calibration validation experiments showed that the proposed absolute luminance meter has the capability of measuring wide range of absolute luminance levels quickly with an average deviation of less than 2 cd/m2 from actual measurements or with 97.48% accuracy

AMHARIC SPEECH RECOGNITION USING JOINT TRANSFORMER AND CONNECTIONIST TEMPORAL CLASSIFICATION WITH CHARACTER-BASED AND SUBWORD-BASED ACOUSTIC AND LANGUAGE MODELS

2024-08-05T08:57:25+00:00

Sequence-to-sequence attention-based models have gained considerable attention in recent times for automatic speech recognition. The transformer architecture has been extensively employed for a variety of sequence-to-sequence transformation problems, including machine translation and automatic speech recognition. This architecture avoids sequential computation that is used in recurrent neural networks and leads to improved iteration rate during the training phase. Connectionist temporal classification, on the other hand, is widely employed to accelerate the convergence of the sequence-to-sequence model by explicitly learning a better alignment between the input speech feature and output label sequences. Amharic language, a Semitic language spoken by 57.5 million people in Ethiopia, is a morphologically rich language that poses a challenge for continuous speech recognition as a root word can be conjugated and inflected into thousands of words to reflect subject, object, tense and quantity. In this research, the connectionist temporal classification is integrated with the transformer for continuous Amharic speech recognition. A speech recognition system is also investigated by utilizing character- based and sub word-based models. The results show that a best character error rate of 8.04 % for the character-based model with character level language model and a best word error rate of 22.31 % for the sub word-based model with sub word-level language model.