Efficient Surrogate Modelling of Nonlinear Aerodynamics in Aerostructural Coupling Schemes

Lindhorst, K.; Haupt, Matthias; Horst, Peter

doi:10.2514/1.j052725

Cited by 43 publications

(29 citation statements)

References 22 publications

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“…The training process consists of two steps and is summarized in the follwing paragraphs, for further information consult [7,8,9]:…”

Section: Training Processmentioning

confidence: 99%

“…Recently [8] presented a reduced order model, that combines proper orthogonal decomposition (POD) and a discrete Markov chain with nonlinear mapping functions for the prediction of aerodynamic loads in the time domain. This paper presents an approach for the direct incorporation of the DVA [6] into this markov chain based ROM and an application to the 3D AGARD445.6 benchmark configuration under a discrete gust.…”

Section: Introductionmentioning

confidence: 99%

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Extension and Application of a Nonlinear Reduced Order Model to Gust Load Prediction in Time Domain

Strobach¹,

Lindhorst²,

Haupt³

et al. 2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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Abstract. This paper aims at extending a markov chain based reduced order model to discrete gust load prediction in an aeroelastic simulation. An method for the incorporation of the disturbance velocity approach is presented and evaluated for the AGARD445 wing based on different training strategies. The reduced order model trained under elastic and gust load conditions can successfully predict the gust response in a rigid and in an elastic setup. Thus the presented ROM approach can serve as one single CFD surrogate model to predict aerodynamic forces under multiple loading conditions.

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“…The training process consists of two steps and is summarized in the follwing paragraphs, for further information consult [7,8,9]:…”

Section: Training Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Extension and Application of a Nonlinear Reduced Order Model to Gust Load Prediction in Time Domain

Strobach¹,

Lindhorst²,

Haupt³

et al. 2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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show abstract

“…In this work even evolving input data is chosen to provide the RBF center c i , due to its simplicity. The radius r i or width is defined as per reference [17]:…”

Section: B Proper Orthogonal Decompositionmentioning

confidence: 99%

“…POD with a Markov-Chain interpolator function and Radial-Basis Function Artificial Neural Network (RBF-ANN) to model nonlinear aerodynamic flows for aero-structural calculations, in this approach the input and output were the POD coefficients of the grid displacement and aerodynamic force distribution [17,18], the authors also suggested that excessive POD modes may degrade the approximation accuracy. Therefore, it is cumbersome to balance the number of POD modes for both input and output.…”

mentioning

confidence: 99%

“…Several of these techniques have been demonstrated to construct nonlinear ROM or surrogate models for aeroleasticity successfully [2,6,14,[16][17][18]; the majority of these have been investigated to provide a nonlinear mapping function for dynamic aeroelastic problems such as LCOs, but at the expense of flow field information. Recently, Yao and Liou [21] proposed a nonlinear model by assembling a set of linear models that are each valid in the vicinity of sampling points, which provides not only the aerodynamic force but also the flow field information for nonlinear aeroelastic modeling.…”

mentioning

confidence: 99%

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Nonlinear Aerodynamic and Aeroelastic Model Reduction Using a Discrete Empirical Interpolation Method

Yao

Marques

2017

AIAA Journal

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A novel surrogate model is proposed in lieu of Computational Fluid Dynamics (CFD) solvers, for fast nonlinear aerodynamic and aeroelastic modeling. A nonlinear function is identified on selected interpolation points by a discrete empirical interpolation method (DEIM). The flow field is then reconstructed using a least square approximation of the flow modes extracted by proper orthogonal decomposition (POD). The aeroelastic reduce order model (ROM) is completed by introducing a nonlinear mapping function between displacements and the DEIM points. The proposed model is investigated to predict the aerodynamic forces due to forced motions using a N ACA 0012 airfoil undergoing a prescribed pitching oscillation. To investigate aeroelastic problems at transonic conditions, a pitch/plunge airfoil and a cropped delta wing aeroelastic models are built using linear structural models. The presence of shock-waves triggers the appearance of limit cycle oscillations (LCO), which the model is able to predict.For all cases tested, the new ROM shows the ability to replicate the nonlinear aerodynamic forces, structural displacements and reconstruct the complete flow field with sufficient accuracy at a fraction of the cost of full order CFD model.

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A model‐based flight qualities evaluation approach for civil aircraft

Zhong

Qu²,

Mora‐Camino

2018

Concurrency and Computation

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SummaryEvaluation of flight qualities plays an important role in the design of a civil aircraft. An appropriate level of flight qualities will be the key to achieve the airworthiness certification. With the objective to provide an overall view of flight qualities evaluation for a civil aircraft, a model‐based approach is proposed. Some terms related to flight qualities are defined formally, and the model‐based flight qualities evaluation approach under different situations is formed and proposed. Two working conditions of actuators are considered in the evaluation of flight qualities. When no actuator fails, linearization is adopted to build a linear flight dynamics model for analyzing the main parameter of flight qualities. When some actuators fail, a new off‐line approach for handling qualities evaluation, which employs a controller that generates appropriate commands for healthy actuators, is proposed. The design of the controller is following the idea of classical predictive control technique, and a recurrent linear quadratic programming problem is formulated to find the maximum remaining maneuverability while not avoiding any constraints. Taking the rotational maneuver as a study example, a test‐bed for handling qualities evaluation is built. The numerical simulation results show the feasibility of proposed evaluation approach.

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Efficient Surrogate Modelling of Nonlinear Aerodynamics in Aerostructural Coupling Schemes

Cited by 43 publications

References 22 publications

Extension and Application of a Nonlinear Reduced Order Model to Gust Load Prediction in Time Domain

Extension and Application of a Nonlinear Reduced Order Model to Gust Load Prediction in Time Domain

Nonlinear Aerodynamic and Aeroelastic Model Reduction Using a Discrete Empirical Interpolation Method

A model‐based flight qualities evaluation approach for civil aircraft

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