Recent years have witnessed rapid development and great indignation burgeoning in the unmanned aerial vehicles (UAV) field. This growth of UAV-related research contributes to several challenges, including inter-communication from vehicle to vehicle, transportation coverage, network information gathering, network interworking effectiveness, etc. Due to ease of usage, UAVs have found novel applications in various areas such as agriculture, defence, security, medicine, and observation for traffic-monitoring applications. This paper presents an innovative drone system by designing and developing a blended-wing-body (BWB)-based configuration for next-generation drone use cases. The proposed method has several benefits, including a very low interference drag, evenly distributed load inside the body, and less radar signature compared to the state-of-the-art configurations. During the entire procedure, a standard design approach was followed to optimise the BWB framework for next-generation use cases by considering the typically associated parameters such as vertical take-off and landing and drag and stability of the BWB. Extensive simulation experiments were performed to carry out a performance analysis of the proposed model in a software-based environment. To further confirm that the model design of the BWB-UAV is fit to execute the targeted missions, the real-time working environments were tested through advanced numerical simulation and focused on avoiding cost and unwanted wastages. To enhance the trustworthiness of this said computational fluid dynamics (CFD) analysis, grid convergence test-based validation was also conducted. Two different grid convergence tests were conducted on the induced velocity of the Version I UAV and equivalent stress of the Version II UAV. Finite element analysis-based computations were involved in estimating structural outcomes. Finally, the mesh quality was obtained as 0.984 out of 1. The proposed model is very cost-effective for performing a different kind of manoeuvring activities with the help of its unique design at reasonable mobility speed and hence can be modelled for high-speed-based complex next-generation use cases.
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http://dx.doi.org/10.3390/s22155477 | DOI Listing |
Nanomaterials (Basel)
January 2025
School of Aeronautical Engineering, Shandong Engineering Research Center of Aeronautical Materials and Devices, Shandong University of Aeronautics, Binzhou 256600, China.
Spray cooling, of which the essence is droplet impacting, is an efficient thermal management technique for dense electronic components in unmanned aerial vehicles (UAVs). Nanofluids are pointed as promising cooling dispersions. Since the nanofluids are unstable, a dispersant could be added to the fluid.
View Article and Find Full Text PDFJ Imaging
January 2025
Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 630090 Novosibirsk, Russia.
Crop field monitoring using unmanned aerial vehicles (UAVs) is one of the most important technologies for plant growth control in modern precision agriculture. One of the important and widely used tasks in field monitoring is plant stand counting. The accurate identification of plants in field images provides estimates of plant number per unit area, detects missing seedlings, and predicts crop yield.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Laboratory for Robot Mobility Localization and Scene Deep Learning Technology, Guizhou Equipment Manufacturing Polytechnic, Guiyang 550025, China.
In recent years, unmanned aerial vehicle (UAV) technology has advanced significantly, enabling its widespread use in critical applications such as surveillance, search and rescue, and environmental monitoring. However, planning reliable, safe, and economical paths for UAVs in real-world environments remains a significant challenge. In this paper, we propose a multi-strategy improved red-tailed hawk (IRTH) algorithm for UAV path planning in real environments.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Technology Research and Development Centre, Xuelong Group Co., Ltd., Ningbo 315899, China.
To address the challenges of slow convergence speed, poor convergence precision, and getting stuck in local optima for unmanned aerial vehicle (UAV) three-dimensional path planning, this paper proposes a path planning method based on an Improved Human Evolution Optimization Algorithm (IHEOA). First, a mathematical model is used to construct a three-dimensional terrain environment, and a multi-constraint path cost model is established, framing path planning as a multidimensional function optimization problem. Second, recognizing the sensitivity of population diversity to Logistic Chaotic Mapping in a traditional Human Evolution Optimization Algorithm (HEOA), an opposition-based learning strategy is employed to uniformly initialize the population distribution, thereby enhancing the algorithm's global optimization capability.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
UniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia.
Insects enhance aerodynamic flight control using the dynamic movement of their appendages, aiding in balance, stability, and manoeuvrability. Although biologists have observed these behaviours, the phenomena have not been expressed in a unified mathematical flight dynamics framework. For instance, relevant existing models tend to disregard either the aerodynamic or the inertial effects of the appendages of insects, such as the abdomen, based on the assumption that appendage dynamic effects dominate in comparison to aerodynamic effects, or that appendages are stationary.
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