A Mode Based Reduced Order Model for Rotorcraft Store Separation

Peters, Nicholas; Wissink, Andrew M.; Ekaterinaris, John A.

doi:10.2514/6.2022-0312

Cited by 5 publications

(4 citation statements)

References 22 publications

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“…The motion trajectory of the store is solved by solving six-degree-of-freedom equation, in which the equation of motion of the centroid is as follows: (20) The relationship between attitude angle and angular velocity is given by Eq. ( 21)…”

Section: Methodsmentioning

confidence: 99%

“…A similarity law between the separation of a heavy store and the unsteady wind tunnel free flight tests of air-launch rockets was derived, is can be used to the research of the separation of a heavy store [17,18]. A modeling method based reduced order model for external store separation is proposed, which can make high fidelity predictions for both surface pressure and shear stress distributions at minimal computational cost [19,20].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Numerical Simulation about the Characteristics of the Store Released from the Internal Bay in Supersonic Flow

Cheng¹,

Si²,

Li³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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To understand the influence of the initial release conditions on the separation characteristics of the store and improve it under high Mach number (Ma = 4) flight conditions, the overset grid method and the Realizable k − ε turbulence model coupled with an equation with six degrees of freedom are used to simulate the store released from the internal bay. The motion trajectory and the attitude angle of the store separation under the conditions of different centroid, velocity, height and control measures are given by the calculated result. Through analysis, the position of the centroid will affect the separation of the store, which needs to be considered in the design. Increasing the launching height is conducive to the separation of the store. If the store has an initial velocity, it can leave the internal bay more quickly and reduce the probability of collision with the wall. Cylindrical rod and slanted aft wall control measures can improve the attitude of the store and make the store fall more smoothly.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Numerical Simulation about the Characteristics of the Store Released from the Internal Bay in Supersonic Flow

Cheng¹,

Si²,

Li³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

View full text Add to dashboard Cite

show abstract

“…Recently, advances in data science and machine learning have provided opportunities to apply these relatively new technologies to CFD. Using modal decomposition, we can approximate the resulting flow field using Proper Orthogonal Decomposition (POD) [5,6], Spectral POD [7], and Dynamic Mode Decomposition (DMD) [8]. Traditionally, such methods have been used to reconstruct flow fields with inputs either from experiments or CFD.…”

Section: Introductionmentioning

confidence: 99%

Data Reduction Technologies in Prediction of Propeller Noise

Afari,

Mankbadi

2024

Aerospace

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High-fidelity computations are often used in predicting the tonal and broadband noise of propellers and rotors associated with Advanced Air Mobility Vehicles (AAMVs). But LES is both CPU and storage intensive. We present here an investigation of the feasibility of reduction methods such as Proper Orthogonal Decomposition as well as Dynamic Mode Decomposition for reduction of data obtained via LES to be used further to obtain additional parameters. Specifically, we investigate how accurate reduced models of the high-fidelity computations can be used to predict the far-field noise. It is found that POD is capable of accurately reconstructing the parameters of interest with 15–40% of the total mode energies, whereas the DMD can only reconstruct primitive parameters such as velocity and pressure loosely. A rank truncation convergence criterion > 99.8% is needed for better performance of the DMD algorithm. In the far-field spectra, DMD can only predict the tonal contents in the lower and mid frequencies, while the POD can reproduce all frequencies of interest.

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“…Recent work has shown that these ROM-based surrogate models are able to retain a high degree of fidelity while operating at a minimal computational cost. Examples of areas of ROM application include heat transfer (Chen et al, 2015), combustion (Chang et al, 2019), turbine blade modeling (Jin et al, 2017), boundary layer ingestion (Cinquegrana and Vitagliano, 2021), and store separation (Peters et al, 2021(Peters et al, , 2022a.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Reduced Order Model for Rotor Optimization

Peters

Silva²,

Ekaterinaris³

2022

Preprint

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Abstract. For rotor design applications, such as wind turbine rotor or Urban Air Mobility (UAM) rotorcraft and flying car design, there is a significant challenge in quickly and accurately modeling rotors operating in complex turbulent flow fields. One potential path for deriving high-fidelity but low-cost rotor performance predictions is available through the application of data-driven surrogate modeling. In this study, an initial investigation is undertaken to apply a proper orthogonal decomposition (POD) based reduced order model (ROM) for predicting rotor distributed loads. The POD ROM was derived based on computational fluid dynamics (CFD) results and utilized to produce distributed pressure predictions on rotor blades subjected to topology change due to variations in twist and taper ratio. Rotor twist, θ, was varied between 0°, 10°, 20°, and 30° while taper ratio, λ, was varied as 1.0, 0.9, 0.8, and 0.7. For a demonstration of the approach, all rotors consisted of a single blade. The POD ROM was validated for three operation cases; a high pitch or a high thrust rotor in hover, a low pitch or a low thrust rotor in hover, and a rotor in forward flight at a low speed resembling wind turbine operation with wind shear. Results showed highly accurate distributed load predictions could be achieved and the resulting surrogate model can predict loads at a minimal computational cost. The computational cost for the hovering blade surface pressure prediction was reduced from 12 hours on 440 cores required for CFD to a fraction of a second on a single core required for POD. For rotor in forward flight cost was reduced from 20 hours on 440 cores to less than a second on a single core. The POD ROM was used to undergo a design optimization of the rotor such that figure of merit was maximized for hovering rotor cases and the lift to drag effective ratio was maximized in forward flight.

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A Mode Based Reduced Order Model for Rotorcraft Store Separation

Cited by 5 publications

References 22 publications

Numerical Simulation about the Characteristics of the Store Released from the Internal Bay in Supersonic Flow

Numerical Simulation about the Characteristics of the Store Released from the Internal Bay in Supersonic Flow

Data Reduction Technologies in Prediction of Propeller Noise

A Data-Driven Reduced Order Model for Rotor Optimization

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