Print ISSN: 1681-6900

Online ISSN: 2412-0758

Volume 41, Issue 7 (Mechanical Engineering)

Volume 41, Issue 7 (Mechanical Engineering), July 2023

Research Paper

Computational Single and Multiphase Approaches to Investigate the Hydrothermal Behavior of Hybrid Nano-fluid in Plain and Wavy Tubes

Ahmed S. Habeeb; Sattar Aljabair; AbdulHassan A. Karamallah

Engineering and Technology Journal, 2023, Volume 41, Issue 7, Pages 1-19
DOI: 10.30684/etj.2023.136449.1316

The newest class of heat transfer improvement is accomplished by using hybrid Nano-fluids. Therefore, the heat transfer and pressure drop of a mixture of Iron oxide (Fe3O4) and Magnesium oxide (MgO) nanoparticles suspended into the base fluid under a turbulent regime through a plain and wavy tube are computed employing commercial software ANSYS Fluent. A mixture of Fe3O4 and MgO nanoparticles in pure water is considered a brand-new type of hybrid Nano-fluid for boosting heat transfer. The simulation procedures were performed utilizing the single and multiphase (mixture) approaches at Reynolds number in the range of (3,916 - 31,331) and volume concentrations range of (0.5% ≤ φ ≤ 2%). The plain and wavy walls are subjected to a constant heat flux of 18,189 W/m2, and the flow is presumed as fully developed. The computed outcomes are validated with the correlation equations and experimental data of literature. The outcomes demonstrate that boosting the nanoadditives fraction leads to a remarkable improvement of heat transfer and hydrothermal performance indicator (HPI) of MgO-Fe3O4 /H2O Hybrid Nano-fluid through the considered tubes compared with the conventional base fluid. However, the increment is slightly higher with a wavy wall tube than with the plain one. Moreover, new correlations were suggested for specific water-based hybrid Nano-fluid volume concentrations.

Experimental and Numerical Study of Spur Gears With Lightening Holes

Almurtadha A. Ahmed; Ali R. Hassan

Engineering and Technology Journal, 2023, Volume 41, Issue 7, Pages 1-11
DOI: 10.30684/etj.2023.134713.1246

The gear is a very important component of power transmission in a flying vehicle and rotating mechanisms etc... In this paper, the dynamic effect and stresses generated as a result of the mash gear will be studied by designing light-weight gears by making lightening holes of multiple diameters (14, 19, 24 and 29) mm at serval speeds (500,1000,1500,2000) that represent the variables parameter with a fixed dimension between the center of the holes and the center of rotation of the gear 43 mm and the number of 5 holes for gears with reduction ratios of gear mass ranging from (3.6%-15%) that represent the constant parameter. The 5-hole gear is better with a hole diameter (0.1085 * Dp) which is equivalent to 19 mm in this research with respect to the gear diameter of 175 mm. Where the maximum value of stress concentration in the root of the tooth reached 0.655 M.N/m^2.

Investigation of Frequency-Domain-Based Vibration Signal Analysis for UAV Unbalance Fault Classification

Luttfi A. Al-Haddad; Alaa A. Jaber; Paramin Neranon; Sinan A. Al-Haddad

Engineering and Technology Journal, 2023, Volume 41, Issue 7, Pages 1-9
DOI: 10.30684/etj.2023.137412.1348

The flying reliability of Unmanned Aerial Vehicles (UAVs) and flying robots, which directly determines the operational degree of safety, is becoming more important in recent intelligent decades. Reliability and a high level of safety are critical for autonomously controlled flying robots, especially in transportation and entertainment applications. Subsequently, monitoring UAV health is crucial and essential for system safety, cost savings, and excellent dependability. The development of numerous monitoring strategies has resulted from the requirement for a simple and accurate unbalance classification procedure. This paper provides an Unbalance Classification and Isolation (UCI) system for multirotor UAV propeller impairments. The technique is based on the processing of signal vectors from a vibration sensor positioned in the lines of the intersection of a modern-day drone's four propulsion units, which supply data for the Fast Fourier Transform (FFT) feature extraction. To identify and locate broken blades, characteristic fault signatures collected from vibration signals are employed and displayed in real-time on the programming platform. A noticeable maximum frequency shifting percentage value of 4.2% is acquired when deviating from a healthy state. The results reveal that identifying and isolating defective rotor states has high sensitivity and outperforms current studies in regard to unbalance classification of UAVs. The adopted technique is an efficient and low-cost solution that can be implemented in any multirotor UAV.