Adama University

About: Adama University is a education organization based out in Nazrēt, Ethiopia. It is known for research contribution in the topics: Population & Adsorption. The organization has 840 authors who have published 1010 publications receiving 5547 citations. The organization is also known as: Adama Science and Technology University & ቴክኖሎጂ ዩኒቨርሲቲ, አዳማ ሳይንስና ቴክኖሎጂ ዩኒቨርሲቲ.

Tractor-Trailer Gap Optimization of a Truck for Reduction of Aerodynamic Drag

Abstract: The major target of automotive industries in the production of vehicles is achieving vehicle fuel consumption. The resources of fossil fuels getting depleted and the prices are increasing. Sino truck is one of the successful vehicles being used in the transportation of goods. There is a need to develop fuel-efficient Sino truck. There are many fuel-saving technologies are tried by researchers and engineers. Out of which designing of the aerodynamic shape of a vehicle for reduction of drag is observed to an important method for fuel be saving. An effort is made for reducing the aerodynamic drag of Sino truck model-321 by modifying the tractor-trailer gap with an aerodynamic shape. The modified Sino truck with different tractor-trailer gap shapes is analyzed using CFD to find their influence on the flow around Sino truck. Also, the analysis was done to identify the critical zones where the drag is more. CFD analysis was done on modified Sino truck by varying trailer and tractor gap, varying the height of the trailer concerning cab, varying the shape of the roof of the trailer and with under trailer coverage. The analysis was done at different speeds from 64 to 96 kmph with 12 m/s crosswinds. Out of all these, it is observed that undercarriage coverage has a great influence in the reduction of drag resistance. Modifications on the rear side of the trailer helped in reducing the separation of the flow separation and in the reduction of drag.

Magnitude and associated factors of low birth weight among term newborns delivered in Addis Ababa public hospitals, Ethiopia, 2021

Abstract: Only 14% of births had information on birth weight available at the time of birth in Ethiopia. Hence, previous studies underestimate the magnitude and associated factors of low birth weight (LBW). As a result, the goal of this study is to fill those gaps in the previous studies. An institution-based cross-sectional study was employed. Binary logistic regression was used to identify the associated factors. In this study, the magnitude of LBW was 13.06%. History of chronic medical illness (AOR = 3; 95% CI: (1.02, 9.17)), haemoglobin level during pregnancy (AOR = 0.23; 95% CI: (0.10, 0.50)), iron/folic acid supplementation (AOR = 0.27; 95% CI: (0.10, 0.72)) and extra meal during pregnancy (AOR = 3.2; 95% CI: (1.52, 7.00)) were significantly associated with LBW. The magnitude of LBW in this study was comparable to the Ethiopian Demographic and Health Survey (EDHS) report from 2016. It is better to intervene in those identified factors in order to reduce LBW.Impact StatementWhat is already knownon this subject? Low birth weight (LBW) accounts for 60-80% of all neonatal deaths each year. In developing countries like Ethiopia, LBW is a major public health concern. Almost half of the world's infants are not weighed at birth, a figure that is especially high in sub-Saharan Africa including Ethiopia.What dothe resultsof this study add? Only 14% of births had information on birth weight available at the time of birth in Ethiopia. Hence, previous studies underestimate the magnitude and associated factors of LBW. To meet the Sustainable Development Goals (SDGs)-2030 targets for neonatal and child mortality, sufficient evidence on the magnitude of LBW and associated factors must be important in order to contribute to the development of timely interventions. A history of chronic medical illness, haemoglobin level, iron/folic acid supplementation and extra meal during pregnancy was associated with LBW.What are the implications of these findings for clinical practice and/or further research? The findings of this study will be useful in developing better health policies to prevent LBW as well as interventions that can target the identified factors.

Formability Evaluation of EN-10149-2 (S700mc) Steel Under In-Plane Plane Stretching Condition

Abstract: The current effort is intended to evaluate the forming behavior of the EN-10149-2 (S700mc) steel of 2.42 mm thickness under in-plane plane-stretching (IPPS) condition at ambient conditions. EN-10149-2 (S700mc) steel has good mechanical properties and lightweight that increase the application in automotive, aerospace, and industrial structural design compared to other metals. For which, the tensile and plain stretching test samples were prepared in three rolling directions 0°, 45°, and 90°. The mechanical properties such as the yield strength, tensile strength, uniform elongation, total elongation, hardening exponent (n-value), material strength coefficient (K) and plastic strain ratio (R-value) of EN-10149-2 (S700mc) steel are evaluated from the tensile testing. The microstructure and hardness of the material were also evaluated. IPPS evaluation test has been carried out by stamping circular grids at the middle of the specimen by which measured the manor and major strain using thickness gradient necking criterion (TGNC). The obtained results from experiments found that the maximum limit strain is appeared for the rolling direction of 45° and followed by 90° and 0°. This indicates that the maximum formability is in 45° rolling direction during the IPPS test.

The 2D resistivity measurement eror and its effect on the model accuracy

Abstract: We examine the measurement noise of electrical resistivity tomography and assess its effect on the inverted results. The observed and numerically simulated resistivity datasets are analyzed regarding noise distributions. We evaluate and present the contact resistance, reciprocal and repeating errors, potential noise, artificial effect on 2D resistivity measurement, inversion misfit, and model accuracy. The result shows considerable measurement noise variation for dry and wet conditions. This study uses a 3% repeatability error cut-off, and about 3.2% of the dry season and 0.83% of the wet season datasets are above cut-off values.  The result also exhibits an inverse relationship between the precipitation and reciprocal error. The resistivity measurement in dry conditions generally indicates high contact resistance, repeatability error, and reciprocal errors, resulting in significant data discarding. We also reveal the misfit between observed and model-predicted resistivity data; a high discrepancy is exhibited for noisy data, leading to substantial model error. The depth of investigation (DOI) threshold depth decrease with increasing measurement noise. This study will give insight into measurement noise evaluation, allow cut-off value, assess data noise propagation and its effects on the data misfits and inverted models, and reduce model misinterpretation.