Aerodynamic Performance Enhancement of Wing Body Micro UAV Employing Blended Winglet Configuration

Tjahjana, Dominicus Danardono Dwi Prija; Yaningsih, Indri; Imama, Billy Yansa Latief; Prabowo, Aditya Rio

doi:10.5109/4742122

Cited by 9 publications

(7 citation statements)

References 24 publications

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“…Gongzhang and Axtellius (2020) [15] numerically compared winglet designs and reported that fenced winglets offered minimal benefit, while sharklets exhibited the best performance among the studied designs. Tjahjana et al (2021) [16] used CFD to identify an optimal blended winglet configuration for micro-UAVs: a taper ratio of 0.3 and a cant angle of 50°, improving the lift-to-drag ratio by 9.84% and reducing the wingtip vortex by 17% compared to the baseline.…”

Section: Literature Review and Research Gapmentioning

confidence: 99%

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Experimental Study of the Effect of Different Winglet Configurations on The Lift and Drag Characteristics of BWB Aircraft

Ishrak,

Shuvo,

Tasnim

et al. 2024

Preprint

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Sustainable aviation is currently a major concern since people are constantly relying on aircraft for transport over long distances in a short amount of time. Newer technologies are constantly being developed to enhance the aerodynamic efficiency of existing aircraft and improve fuel conservation. Winglets are one such technology. Our research focuses on how different winglet designs affect the lift and drag characteristics of blended-wing body aircrafts; the concept of these designs is currently being researched and compared to that of the base model with no winglet. The models were subjected to both computational and experimental analyses at three different velocities and six angles of attack to determine the lift and drag values resulting from various winglet configurations. The results showed that Split Fence had the best performance in both computational and experimental analyses, with an L/D of 10.608 at a 5° angle of attack during the CFD analysis compared to 5.52 for the base model. The Spikelet and the Spike Scimitar Winglet also showed high aerodynamic efficiency. The C-Winglet, however, showed poorer performance than did the other winglets. The insights from this research can help optimize winglet designs and explore the design of BWB aircraft, leading to substantial reductions in fuel consumption and carbon emissions in the aviation industry.

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Section: Literature Review and Research Gapmentioning

confidence: 99%

“…Several studies have evaluated the performance of blended and cant winglets [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. In most cases, the design is quite simple.…”

Section: Spikeletmentioning

confidence: 99%

Experimental Study of the Effect of Different Winglet Configurations on The Lift and Drag Characteristics of BWB Aircraft

Ishrak,

Shuvo,

Tasnim

et al. 2024

Preprint

View full text Add to dashboard Cite

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“…So, all information from different sources will be shown on the Google Home page 65) suggesting information about the knowledge graph 66) . The next section explains the proposed framework for gathering the recent trends in the Knowledge graph research field for the number of scientific articles found in this field and the major areas/regions/countries that contributed more to this field 67) .…”

Section: Knowledge Graphmentioning

confidence: 99%

Graph Based Analytics and Review of Knowledge Graph Field by Using Two Decade Data- Finding Paradigms and Opportunities

Yadav,

Gopinathan

2024

Evergreen

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Knowledge Graph Embedding (KG Embed) has an important role in extracting the query and retrieving the required information in the technology specifically in scientific research. A surge is seen in the growth of knowledge graphs and also in knowledge representation and reasoning. This paper with the help of the knowledge graph creation helps in finding the hottest topic for research, Specifically, this study includes four research repositories that are Google Scholar (GS), IEEE Xplore, Science, and Worldwide Science (WWS). This study is based on keyword searching, which includes four keywords that are Knowledge graph (KG), Knowledge graph embedding (KG Embed), Recommendation system knowledge graph (RS KG), and Recommendation system in the education domain (RS in education). The data of several papers, articles, and books present in these four repositories from 2000 to 2022 is collected using these four keywords. After this, the paper visualizes this data using graphs and knowledge graphs with the help of parameters like centrality and clustering, which shows that Google Scholar contains more data than other repositories and the hottest topic in research is knowledge graph. It also gives an overview of how a knowledge graph is used in the recommendation system and how it is helpful. Based on the result that we got through the visualization of graphs and knowledge graphs; this study summarizes the suggestions and directions for researchers and practitioners to do future research on knowledge graphs by keeping all the related studies and points. This research takes into account the knowledge Graph research papers, articles, books, and theses from these four sources.

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“…Prior studies have explored drone parameters [33][34][35][36][37][38] such as their integrity, identification, and performance. Similar to a commercial airplane, the drone also maneuvers in three directions as shown in Figure 2.…”

Section: Drone Axes and Rotationmentioning

confidence: 99%

Exploratory Study of Drone Data Stabilization with Implications in Vibration-based Structural Health Monitoring

Ngeljaratan,

Mohamed A. Moustafa,

Sumarno

et al. 2023

Evergreen

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This exploratory study presents stabilization approaches of drone-based videos with implications in vibration-structural health monitoring applications. Unlike other standalone visionbased systems such as cameras placed on a tripod, drone drifting may occur due to airborne missions especially when operated indoors or in lower altitudes. It affects the captured frames and even the slightest movement of the drone camera will reduce the data accuracy. Post-processing methods using Computer Vision (CV) and signal-processing algorithms are used in this study to explore their effectiveness and accuracy in measuring the dynamic vibration of a structure. The object study is an aluminum bar subjected to two sinusoidal vibrations then recorded using a camera embedded on a quadcopter. After video acquisition, the post-processing is started by image enhancement and scaling procedures, followed by Scale Invariant Transform (SIFT) feature detection, extraction, and matching. The scaling factor is used to convert the image coordinate to an object coordinate system before computing the displacement of the object. Data stabilization techniques are implemented in this study, first is the background subtraction method to eliminate signal drifting and second is cleaning the data from any trends. The accuracy of the proposed framework is tested by comparing the structural dynamic responses from drone measurement to a reference sensor. The Autoregressive (AR) model generated the Power Spectral Density of the signal is also compared to the measurement from a reference camera. The results show the high accuracy of the proposed method which is up to 97.52% on the dynamic response with less effect on the signal PSD. Overall, the exploratory study obtains satisfactory results and provides a new alternative to an intelligent system in the structural health monitoring field.

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Aerodynamic Performance Enhancement of Wing Body Micro UAV Employing Blended Winglet Configuration

Cited by 9 publications

References 24 publications

Experimental Study of the Effect of Different Winglet Configurations on The Lift and Drag Characteristics of BWB Aircraft

Experimental Study of the Effect of Different Winglet Configurations on The Lift and Drag Characteristics of BWB Aircraft

Graph Based Analytics and Review of Knowledge Graph Field by Using Two Decade Data- Finding Paradigms and Opportunities

Exploratory Study of Drone Data Stabilization with Implications in Vibration-based Structural Health Monitoring

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