Characteristics of the shedding vortex around the Coanda surface and its impact on circulation control airfoil performance

Sun, Quanbing; Shi, Zhiwei; Sun, Zhikun; Chen, Sinuo; Chen, Yongliang

doi:10.1063/5.0139806

Cited by 7 publications

(2 citation statements)

References 27 publications

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“…Flap Position (𝑠̄0): our study indicates better lift coefficients with trailing-edge flaps at low α. This aligns with the Coanda effect [9],…”

Section: − Low Angle Of Attack (α)supporting

confidence: 86%

Optimizing Aerodynamic Efficiency in Subsonic Flows: A Parametric Analysis of Bio-Inspired Flaps using Asymptotic Methods

Eddegdag,

Naamane,

Radouani

et al. 2023

Preprint

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This research is focused on optimizing aircraft performance by harnessing the principles of avian covert feathers, specifically through the passive control of subsonic laminar incompressible boundary layers on airfoils. The exigency of this study is rooted in the growing need for more aerodynamically efficient aircraft, especially in light of increasing fuel costs and environmental concerns. To achieve this, the study employs a robust mathematical framework that amalgamates asymptotic methods, perturbation techniques, and triple-deck boundary layer theory, aiming for a rigorous quantification of aerodynamic behavior under various flight conditions. Three key parameters are meticulously scrutinized: the corrective parameter b, the flap position s0, and the flap angle β. These parameters are analysed for their impact on the lift (Cl) and drag (Cd) coefficients over a range of angles of attack (α). A notable outcome of this research is the identification of b as a pivotal variable that plays a stabilizing role in the aerodynamic system. Through extensive asymptotical modelling and non-linear stability analysis, it was deduced that b is indispensable for managing lift-to-drag ratios effectively across fluctuating flight conditions. To translate these theoretical findings into practical applications, the study introduces a comprehensive parametric landscape. This landscape serves as a decision-making tool by outlining how the parameters s0 and β behave across varying α scenarios, thereby providing actionable insights for airfoil configuration. Importantly, these results bear significant implications for the aerospace industry. They offer a pathway for the development of more efficient airfoils that promise reduced drag and, consequently, diminished fuel consumption.

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“…Flap Position (𝑠̄0): our study indicates better lift coefficients with trailing-edge flaps at low α. This aligns with the Coanda effect [9],…”

Section: − Low Angle Of Attack (α)supporting

confidence: 86%

Optimizing Aerodynamic Efficiency in Subsonic Flows: A Parametric Analysis of Bio-Inspired Flaps using Asymptotic Methods

Eddegdag,

Naamane,

Radouani

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…As schematically illustrated in Figure 1ac, we propose to create AI systems that would exploit physical phenomena that either surround human-made machines, including aeroplanes, boats and cars, or are induced by their movement. For example, such AI systems would do certain computations employing turbulence in the atmosphere that forms behind an aeroplane or UAV [16,17]. Similarly, in the case of a boat or a submersible ROV, an AI system could use water waves and other fluid-mechanical phenomena such as the formation of bubbles [18,19] and vortices [20,21] in water.…”

Section: What Is This Review Article About?mentioning

confidence: 99%

Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspective

Abbas,

Abdel-Ghani,

Maksymov

2024

Preprint

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Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-driving cars may consume up to 50% of total power available onboard, thereby limiting the vehicle’s range of functions and considerably reducing the distance the vehicle can travel on a single charge. Next-generation onboard AI systems need an even higher power since they collect and process even larger amounts of data in real time. This problem cannot be solved using the traditional computing devices since they become more and more power-consuming. In this review article, we discuss the perspectives of development of onboard neuromorphic computers that mimic the operation of a biological brain using nonlinear-dynamical properties of natural physical environments surrounding autonomous vehicles. Previous research also demonstrated that quantum neuromorphic processors (QNPs) can conduct computations with the efficiency of a standard computer while consuming less than 1% of the onboard battery power. Since QNPs is a semi-classical technology, their technical simplicity and low, compared with quantum computers, cost make them ideally suitable for application in autonomous AI system. Providing a perspective view on the future progress in unconventional physical reservoir computing and surveying the outcomes of more than 200 interdisciplinary research works, this article will be of interest to a broad readership, including both students and experts in the fields of physics, engineering, quantum technologies and computing.

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Sediment erosion characteristics of Pelton turbine runner: Effects of sediment concentration and diameter

Li,

Lu,

Gong

et al. 2024

Renewable Energy

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Characteristics of the shedding vortex around the Coanda surface and its impact on circulation control airfoil performance

Cited by 7 publications

References 27 publications

Optimizing Aerodynamic Efficiency in Subsonic Flows: A Parametric Analysis of Bio-Inspired Flaps using Asymptotic Methods

Optimizing Aerodynamic Efficiency in Subsonic Flows: A Parametric Analysis of Bio-Inspired Flaps using Asymptotic Methods

Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspective

Sediment erosion characteristics of Pelton turbine runner: Effects of sediment concentration and diameter

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