Efficient accelerators for PSO in an inverse design of multi-element airfoils

Pehlivanoglu, Y. Volkan

doi:10.1016/j.ast.2019.05.028

Cited by 22 publications

(8 citation statements)

References 22 publications

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“…They were unable to predict attached flow in the front portion of the flap (gap vicinity) as shown in Figure 10. S-A, probably the most popular turbulence model used in multi-element aerofoil applications, 11,14,19,21,26--28,34,35,47 can boast very good C L ( α ) match (except stall mechanism) but overpredicts drag, especially for α > 10° as well as underestimate slightly CLα derivative. Another transitional model -- k-kl-ω severely overpredicts C L but reproduces faithfully C L ( α ) shape (it is translated upright) and it is quite good in C D prediction when α is up to 10°.…”

Section: Resultsmentioning

confidence: 99%

“…Unfortunately, multi-element aerofoil has the potential to have multiple local minima in the case of segment arrangement optimization. 28 Gradient-free, heuristic methods are one of the available solutions for circumventing that issue. Benini et al.…”

Section: Introductionmentioning

confidence: 99%

“…29 Finally, state-of-the-art, particle swarm optimization (PSO) method was used by Pehlivanoglu in the inverse design of high-lift promoting multi-element aerofoil. 28…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimization of the three-segment aerofoil arrangement based on wind tunnel tests and numerical analysis

Grendysa

Olszański

2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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This paper presents the optimization of multi-element aerofoil for the LAR-3 Puffin -- STOL light transport aircraft concept proposal. Based on the geometry and aerodynamic characteristics of the well-known and proven in flight three-segment NACA 63A416 aerofoil, the authors explore the possibility of enhancing its high-lift performance by the movement of slot and flap position in extended (deployed) aerodynamic configuration. In order to determine the optimum positions of aerofoil segments (elements), a multi-step optimization approach was developed. It combines computational fluid dynamics simulations that were used for design space screening and preliminary optimization together with low-turbulence wind tunnel tests which yielded certain results. To decrease the numerical cost of the computer simulation campaign, Design of experiment methods (optimal space-filling design among others) were employed instead of exhausting full factorial (parametric) design. Response surface models of major aerodynamic coefficients (lift, drag, pitching moment) at predicted maximum lift coefficient ( C L max) point allowed to narrow down search space and identify several candidates for optimal configuration to be checked experimentally. Wind tunnel tests campaign confirmed the major trends observed in computational fluid dynamics derived response surface contour plots. For the optimum aerodynamic configuration, chosen experimental C L max is over 3.9, which is a 10% increase over the baseline (initial slat and flap positions) case. In parallel, the maximum lift-to-drag ratio gain at that point was almost 19%. The research outlined in this paper was conducted on behalf of the aircraft production company and its results will be applied in a newly designed transport aircraft.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimization of the three-segment aerofoil arrangement based on wind tunnel tests and numerical analysis

Grendysa

Olszański

2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…For example, a series of airworthiness requirements enforce multiple boundaries to the design space of commercial aircraft wings, especially in take-off, climb, and landing flight regimes where the high-lift device (HLD) has to be used due to lack of sufficient lifting force. 1 Previous studies of HLD design involve lift drag ratio increasing, 2 passive flow controlling, 3 stall lift robustness design, 4,5 and noise reducing. 6 However, as the lifting force increases, aerodynamic load may be redistributed.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic surrogate model based on deep long short-term memory network: An application on high-lift device control

Zhang

Wang

Sun

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part G:

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An unsteady aerodynamic surrogate model based on the deep LSTM (long short-term memory) network is proposed for predicting unsteady aerodynamic coefficients. Deflection angles and deflection velocities of control surfaces are introduced to input values of the surrogate model to enhance the capability of identifying different motion states so that accumulative error can be controlled. Longitudinal stability is extremely important for flight safety while few studies have worked on unsteady aerodynamics of airfoils/wings with moving high-lift device (HLD) motion. Longitudinal static margin sequence of the HLD extending process is studied, and nonlinearity and hysteresis of coefficients in HLD motion are validated. The surrogate model is then applied in HLD motion control with the particle swarm optimization (PSO) method. Additionally, the results are then performed in three-dimensional aircraft HLD control. Validation computations show that longitudinal stability of optimized configuration is promoted with lift coefficient unchanged.

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“…Many optimization methods have been proposed for fixed-wing aircraft [6,7] Airframe system and helicopters [8], but the design optimization research for multicopters is scarce. Most studies focused on optimizing the designs of specific components (e.g., motors, propellers, airfoil shapes, and fuselage aerodynamics) to achieve longer flight endurance [9,7,10]. For example, a propeller efficiency analysis and optimization methods are studied in [11,12], and a motor efficiency analysis and design methods are studied in [13].…”

Section: Introductionmentioning

confidence: 99%

Design Automation and Optimization Methodology for Electric Multicopter UAVs

Dai¹,

Quan²,

Cai³

2019

Preprint

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The traditional multicopter design method usually requires a long iterative process to find the optimal design based on given performance requirements. The method is uneconomical and inefficient. In this paper, a practical method is proposed to automatically calculate the optimal multicopter design according to the given design requirements including flight time, altitude, payload capacity, and maneuverability. The proposed method contains two algorithms: an offline algorithm and an online algorithm. The offline algorithm finds the optimal components (propeller and electronic speed controller) for each motor to establish its component combination, and subsequently, these component combinations and their key performance parameters are stored in a combination database. The online algorithm obtains the multicopter design results that satisfy the given requirements by searching through the component combinations in the database and calculating the optimal parameters for the battery and airframe. Subsequently, these requirement-satisfied multicopter design results are obtained and sorted according to an objective function that contains evaluation indexes including size, weight, performance, and practicability. The proposed method has the advantages of high precision and quick calculating speed because parameter calibrations and time-consuming calculations are completed offline. Experiments are performed to validate the effectiveness and practicality of the proposed method. Comparisons with the brutal search method and other design methods demonstrate the efficiency of the proposed method.

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Efficient accelerators for PSO in an inverse design of multi-element airfoils

Cited by 22 publications

References 22 publications

Optimization of the three-segment aerofoil arrangement based on wind tunnel tests and numerical analysis

Optimization of the three-segment aerofoil arrangement based on wind tunnel tests and numerical analysis

Aerodynamic surrogate model based on deep long short-term memory network: An application on high-lift device control

Design Automation and Optimization Methodology for Electric Multicopter UAVs

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