Dynamic Response of Aeroservoelastic Systems to Gust Excitation

Karpel, Moti; Moulin, Boris; Chen, P. C.

doi:10.2514/1.6678

Cited by 87 publications

(36 citation statements)

References 7 publications

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“…To obtain a state-space representation, a rational function approximation (RFA) of the unsteady aerodynamic influence coefficient matrix is performed with a number of six poles [21]. To capture the spiral nature of the gust column, the approach from Karpel et al [22] is used: The gust model is divided into 20 zones, each having its own reference point. The time delay between the collocation point and the preceding reference point is considered in the RFA.…”

Section: Considered Aeroelastic Modelmentioning

confidence: 99%

Efficient Determination of Worst-Case Gust Loads Using System Norms

Knoblach

Looye

2017

Journal of Aircraft

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Section: Considered Aeroelastic Modelmentioning

confidence: 99%

Efficient Determination of Worst-Case Gust Loads Using System Norms

Knoblach

Looye

2017

Journal of Aircraft

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“…with [ = − & ' I , ⁄ J F and assumed to be zero [15] to avoid the second time derivative of the gust velocity, which may be unsuitable when the excitation is continuous turbulence as it can introduced a white-noise derivative into the model. The unsteady GAF of the control surfaces are instead cast into time-domain through a quasi-steady approximation, which reads…”

Section: Aeroelastic Equations Of Motionmentioning

confidence: 99%

“…The GAF of the gust ) is approximated independently with the same expression. This approach allows for a greater flexibility in the selection of gust aerodynamic poles and increases the fitting accuracy, an important consideration because the gust GAF is known to show a spiral behavior at high reduced frequencies in the RealImaginary plane, difficult to approximate with rational polynomials, due to the penetration term [15]. Although the choice of Roger's RFA and the independent fitting of the gust GAF leads to a state-space model whose size is greater compared to the Minimum-State method by Karpel [18], the model is afterwards reduced to a considerably smaller size through Model Order Reduction.…”

Section: Extended Rational Function Approximation Approachmentioning

confidence: 99%

Parametric reduced order model approach for rapid dynamic loads prediction

Castellani¹,

Lemmens

Cooper³

2016

Aerospace Science and Technology

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A parametric reduced order methodology for loads estimation is described that produces a fast and accurate prediction of gust and manoeuvre loads for different flight conditions and structural parameter variations. The approach enables efficient prediction of the peak loads whilst maintaining the correlated time histories for different loads. It is then possible to determine correlated loads plots with reduced computation without losing accuracy. The effectiveness of the methodology is demonstrated by considering loads arising from families of gusts and pitching manoeuvres acting upon a numerical transport aircraft aeroservoelastic model with varying flight conditions and structural properties.

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“…The optimized RFA shows most of its benefit particularly for the approximation of the gust aerodynamic force matrix . It is known that the terms of this matrix show a spiral behavior at high reduced frequencies in the Re-Im plane, due to the penetration term, that are difficult to approximate with rational polynomials [16]. The optimization of the poles introduces additional design variables which can be tuned to improve the curve fitting.…”

Section: Optimized Rational Function Approximationmentioning

confidence: 99%

Reduced Order Model Approach for Efficient Aircraft Loads Prediction

Castellani¹,

Lemmens²,

Cooper³

2015

SAE Int. J. Aerosp.

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms Page 1 of 9 2015-01-0066 Reduced Order Model Approach for Efficient Aircraft Loads PredictionAuthor, co-author (Do NOT enter this information. It will be pulled from participant tab in MyTechZone)Affiliation (Do NOT enter this information. It will be pulled from participant tab in MyTechZone) AbstractFlight loads calculations play a fundamental role in the development and certification of an aircraft and have an impact on the structural sizing and weight. The number of load cases required by the airworthiness regulations is in the order of tens of thousands and the analysis must be repeated for each design iteration. On large aircraft, CS-25 explicitly requires taking into account for loads prediction, airframe flexibility, unsteady aerodynamics and interaction of systems and structure, leading to computationally expensive numerical models. Thus there is a clear benefit in speeding-up this calculation process. This paper presents a methodology aiming to significantly reduce the computational time to predict loads due to gust and maneuvers. The procedure is based on Model Order Reduction, whose goal is the generation of a Reduced Order Model (ROM) able to limit the computational cost compared to a full analysis whilst retaining accuracy. The method is applied to a commercial transport aircraft modeled with beam elements, unsteady aerodynamics based on Doublet Lattice Method and servo-hydraulic actuators for the control surfaces. The aeroelastic equations of motion are formulated in the time-domain, through the Rational Function Approximation and application of the Balanced Truncation method. The results obtained with the reduced model shows a very good accuracy with respect to the full model and a significant saving in computational time. The impact of flexibility on the gust load factor is also highlighted, comparing it with the quasi-static analysis by Pratt's formula, current standard for Part 23 aircraft.

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Dynamic Response of Aeroservoelastic Systems to Gust Excitation

Cited by 87 publications

References 7 publications

Efficient Determination of Worst-Case Gust Loads Using System Norms

Efficient Determination of Worst-Case Gust Loads Using System Norms

Parametric reduced order model approach for rapid dynamic loads prediction

Reduced Order Model Approach for Efficient Aircraft Loads Prediction

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