Reengineering of the aircraft structural life prediction process to fully exploit advances in very high performance digital computing is proposed. The proposed process utilizes an ultrahigh fidelity model of individual aircraft by tail number, a Digital Twin, to integrate computation of structural deflections and temperatures in response to flight conditions, with resulting local damage and material state evolution. A conceptual model of how the Digital Twin can be used for predicting the life of aircraft structure and assuring its structural integrity is presented. The technical challenges to developing and deploying a Digital Twin are discussed in detail.

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Reengineering Aircraft Structural Life Prediction Using a Digital Twin

Applications of the unsteady vortex-lattice method in aircraft aeroelasticity and flight dynamics

An evaluation of computational models is carried out for flight dynamics simulations on low-speed aircraft with very-flexible high-aspect ratio wings. Structural dynamic models include displacement-based, strain-based, and intrinsic (first-order) geometrically-nonlinear composite beams, while thin-strip and vortex lattice methods are considered for the unsteady aerodynamics. It is first shown that all different beam finite element models (previously derived in the literature from different assumptions) can be consistently obtained from a single set of equations. This approach has been used to expand existing strain-based models to include shear effects. Comparisons are made in terms of numerical efficiency and simplicity of integration in flexible aircraft flight dynamics studies. On the structural modeling, it was found that intrinsic solutions can be several times faster than conventional ones for aircraft-type geometries. For the aerodynamic modeling, thin-strip models based on indicial airfoil response are found to perform well in situations dominated by small amplitude dynamics around large quasi-static wing deflections, while large-amplitude wing dynamics require three-dimensional descriptions (e.g. vortex lattice).

Structural and Aerodynamic Models in Nonlinear Flight Dynamics of Very Flexible Aircraft

Analysis of Nonlinear Control Systems

A new structural modeling concept, the Airframe Digital Twin, for designing and maintaining airframes is proposed. The Airframe Digital Twin is a tail number specific computational model of an individual aircraft. It has the potential to improve the way U.S. Air Force aircraft are managed over their entire lifecycle by creating individualized structural management plans. The Airframe Digital Twin can provide configuration control for each aircraft in the inventory. Through computational simulations performed with an Airframe Digital Twin, it can serve as a virtual health sensor, and provide a forecast of future maintenance needs for an individual aircraft. The Airframe Digital Twin concept is considered possible because of advances in high performance computing. An essential part of the Airframe Digital Twin is the ability to reduce the uncertainty in the model with increasing service experience through Bayesian updating.

The Airframe Digital Twin: Some Challenges to Realization

The investigation of aeroelastic/aeroservoelastic stability through flight testing is an essential part of aircraft certification. The stability boundary prediction is especially difficult when the instability is associated with nonlinearities in the dynamics. An approach is presented for the characterization of the nonlinear dynamics by noniterative identification algorithms. Two different block-oriented nonlinear models are considered to augment existing linear models with nonlinear operators derived by analyzing experimental data. Specifically, focuse is placed on the identification of Hammerstein or Wiener block-oriented models from a N-point data record {¯k, ¯ yk} N = 1 of observed input‐output measurements from an aeroelastic/aeroservoelastic system. Central in the identification of block-oriented models is the use of an a priori set of orthonormal bases tuned with the dynamics of the aeroelastic/aeroservoelastic system. In both cases, a method is proposed to generate the orthonormal bases that is based on the cascade of input-normal balanced state-space realizations of all-pass filters. Case studies with a simulated structurally nonlinear prototypical two-dimensional wing section and actual F/A-18 active aeroelastic wing ground vibration test data are presented.

Nonlinear aeroelastic/aeroservoelastic modeling by block-oriented identification

Morphing aircraft are conceived as multirole platforms that modify their external shape substantially to adapt to a changing mission environment The dynamic response of the unmanned aerial vehicle will be governed by the time-varying aerodynamic forces and moments which will be a function of the wing's shape changes by the morphing command. Here, it is assumed that the morphing unmanned aerial vehicle behaves as a variable geometry rigid body, but with dynamic coefficients corrected to include quasi-steady aeroelastic effects. A multiloop controller for the aeroelastic morphing unmanned aerial vehicle concept is formulated to provide both proven structural and self-scheduled characteristics. The proposed controller uses a set of inner-loop gains to provide stability using classical techniques, whereas a linear parameter-varying outer-loop controller is devised to guarantee a specific level of robust stability and performance for the time-varying dynamics. Reduced-order controllers are synthesized using a robust control reduction technique. A series of maneuvers are devised to exhaustively evaluate the performance of the synthesized multiloop controller subject to large-scale geometrical shape changes. The underlying multiloop approach successfully enables in-flight transformation between vehicle states in less than one minute, while maintaining the overall vehicle stability and control.

Modeling and Control of an Aeroelastic Morphing Vehicle

A unified aeroelastic and flight dynamic formulation is sought to take into account the influence of aeroelastic effects on the flight dynamic behavior of the whole aircraft in a format fully compatible with the aeroelastic, flight dynamics, and automatic control disciplines. By allowing the inclusion of gravity-related terms, vertical acceleration-related aerodynamic stability derivatives, and lift and drag forces due to forward-velocity perturbations into the rational function approximation matrices, the traditional quasi-steady flight dynamic equations of motion are fully recovered. Closed-form solutions are presented for translational and rotational degrees of freedom in the aeroelastic model. The General Atomics-Aeronautical Systems (GA-ASI) Predator® unmanned aerial vehicle is used to numerically demonstrate the unified aeroelastic modeling framework. The results indicate that this approach reproduces, with a high degree of fidelity, the underlying quasi-steady flight dynamic model when no elastic modes are included in the aeroelastic model. Comments are provided to determine the approximate number of elastic modes that need to be included in the aeroelastic model to accurately model its flight dynamic behavior.

Unified Aeroelastic and Flight Dynamic Formulation via Rational Function Approximations

Flight testing for envelope expansion remains dangerous and costly because of difficulties in accurately predicting the onset of flutter. Approaches have been developed that are able to identify optimal models of the aeroelastic dynamics based on flight data but are not able to predict the responses at all airspeeds. Those previous approaches are extended to include parameter variations in the optimal models. Specifically, parameter-varying models of Volterra kernels are identified for inclusion with theoretical models in aeroelastic analysis. The new approach is applied to a pitch‐plunge system to demonstrate the accuracy achieved in predicting the onset of flutter by analyzing data obtained at lower airspeeds.

Identifying Parameter-Dependent Volterra Kernels to Predict Aeroelastic Instabilities

The investigation of utter and aeroservoelastic stability through igh t testing is an essential part of aircraft certication. The stability boundary prediction is especially difcult when the instability is associated with nonlinearity in the dynamics. This paper presents an approach for the characterization of the nonlinear dynamics by non-iterative identication algorithms. Two dieren t block-oriented nonlinear models are considered in this work. Specically , we focused on the identication of Hammerstein and nonlinear feedback models from a N-point data record fuk; ykgN=1 of observed input-output measurements from an aeroelastic system. In the nonlinear feedback case, we propose a method to generate the orthonormal bases that is based on the cascade of input-normal balanced state-space realizations of all-pass lters. We present an application of this nonlinear aeroelastic modeling setup to a structurally nonlinear prototypical two-dimensional wing section.

Dario H. Baldelli

Papers

Nonlinear aeroelastic/aeroservoelastic modeling by block-oriented identification

Modeling and Control of an Aeroelastic Morphing Vehicle

Unified Aeroelastic and Flight Dynamic Formulation via Rational Function Approximations

Identifying Parameter-Dependent Volterra Kernels to Predict Aeroelastic Instabilities

Nonlinear Aeroelastic Modeling by Block-Oriented Identification