Applied Mechanics and Materials
Vol. 934
Vol. 934
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Vol. 933
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Applied Mechanics and Materials
Vol. 932
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Applied Mechanics and Materials
Vol. 931
Vol. 931
Applied Mechanics and Materials
Vol. 930
Vol. 930
Applied Mechanics and Materials
Vol. 929
Vol. 929
Applied Mechanics and Materials
Vol. 928
Vol. 928
Applied Mechanics and Materials
Vol. 927
Vol. 927
Applied Mechanics and Materials
Vol. 926
Vol. 926
Applied Mechanics and Materials
Vol. 925
Vol. 925
Applied Mechanics and Materials
Vol. 924
Vol. 924
Applied Mechanics and Materials
Vol. 923
Vol. 923
Applied Mechanics and Materials
Vol. 922
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Applied Mechanics and Materials Vol. 931
DOI:
https://doi.org/10.4028/v-tjQOv5
DOI link
ToC:
Paper Title Page
Abstract: Solar energy is an abundant and free source of sustainable energy. The objective of this project was to construct and examine smart, standalone photovoltaic (PV) street lighting in Kepyar Village, a rural community located in Wonogiri Regency, Central Java. The intelligent, standalone PV-based lighting system consisted of a 5-meter streetlight pole outfitted with a 60 Wp monocrystalline solar panel system and an Internet of Things (IoT) system. In 2024, measurements were taken in August and September. The system was able to capture energy from sunlight from 6 a.m. until 5 p.m. The average amount of daily energy stored was 144 and 148 Wh, respectively, allowing it to power the street lights for around 7 hours. The findings also revealed that installing standalone PV-based street lighting can provide significant community advantages.
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Abstract: A numerical study of an axial fan was conducted, with models compared to catalogue data, key results discussed, and performance improvement suggestions proposed. Research aims to numerically analyze a five-blade axial fan, using topology optimization to maximize flow rate and minimize blade count by comparing fans with varying blades to identify the optimal design. The five-blade axial fan was designed using Creo PTC Software based on standard requirements, and its numerical analysis was conducted using Computational Fluid Dynamics in ANSYS Workbench (2022 R1). The simulation results for the five-blade fan were validated against catalogue data and compared with fans having 1-7 blades. Results, presented through various contour plots and velocity streamlines, showed that the maximum airflow rate (ṁ = 1.432 kg/s) occurred with four blades, the highest-pressure contour (Ttotal = 474 kPa) with six blades, and the highest total pressure contour (Ttotal = 170 kPa) at the hub with three blades. The maximum velocity contour (V= 30 m/s) and velocity streamline at the stationary frame (V= 35 m/s) were recorded with five blades. Overall, comparing the four-blade results with the other cases shows that the four-blade configuration delivers superior performance under the same model setup and can be used to enhance future designs.
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Abstract: Unmanned aerial vehicles (UAVs) are considered one of the modern technologies that have recently used in many military and civilian applications. This research investigates the aerodynamic stability of the STU.1.M predator drone was studied by studying the change in the values of the lift and drag coefficients and the lift-to-drag ratio using numerical modelling, Computational Fluid Dynamics (CFD) was employed to simulate performance across range of angles of attack (0° to 14°) at various speeds (20, 40, 60, 80 m/sec) under incompressible flow conditions. The engineering model of the aircraft was generated and the numerical validity was confirmed against experimental data from referenced study. The results indicated that the change in the value of the lift and drag coefficients and the lift-to-drag ratio with respect to UAV velocity is with no significant. The results also showed that the value of the lift coefficient and the lift-to-drag ratio increased with the increase in the value of the angle of attack, The maximum L/D ratio of 8.5 was achieved at a 6° angle of attack and speed of UAV 80 m/s, pressure and velocity contours identified stagnation regions with maximum pressure points at the UAV 's nose, wing, and tail.
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