This paper presents a high-fidelity aeroelastic study of the the Multi-Utility Technology Testbed (MUTT) X-56A, designed to exhibit aeroelastic instabilities such as body free flutter (BFF). The primary objective of this work is to assess the use of high-fidelity CFD-based aeroelastic simulations for flutter prediction. This research was originally conducted as part of the Third Aeroelastic Prediction Workshop (AePW3) aiming to enhance the knowledge in aeroelastic predictions using mid to high-fidelity computational aerodynamics. This particular study details the contribution from the Flight Physics & Loads group at the Netherlands Aerospace Centre (NLR), exploring two computation methods for generating the Generalised Aerodynamic Forces (GAFs), namely, ZAERO solver (ZONA Technology) using higher-order panel code ZONA6, and an unsteady RANS-based Computational Fluid Dynamics (CFD) and Computational AeroElastic (CAE) simulations implemented within NLR's ENFLOW simulation system for multi-block flow domains. The high-fidelity CFD and CAE analyses were performed using the flow solver ENSOLV with unsteady Reynolds-Averaged Navier-Stokes (RANS) flow formulation implemented with Explicit Algebraic Reynolds Stress Model (EARSM) turbulence modelling based on the TNT $k-\omega$. The CAE computational procedure consists of four tool chains, involving structural dynamics (modal) analyses; grid interpolation procedure; steady CFD computations on the undeformed shape; unsteady CFD computations on a deforming grid under prescribed, small-amplitude sinusoidal excitations based on the structural mode shapes; and the transformation of the time-domain unsteady solutions to frequency domain in order to construct the GAF matrices. The X-56A configuration used for this study is the 10lb fuel state model released within the AePW-3 group. The resulting GAFs were compared to the ZAERO results, showing good agreement for both the rigid body and elastic modes. Earlier work on X-56A within AePW-3 conveyed the need for further refinement of the high-fidelity aeroelastic methodology. Improvement efforts in this regard, included alternative structural dynamics methods for modal model computations, CFD grid refinements, and adjustments to the (un)steady CFD/CAE simulation procedures and methods.

The X-56 is a Unmanned Aerial Vehicle developed and build by Lockheed Martin in 2013 with the intention to learn more about certain flutter phenomena and active flutter suppression. The UAV is of the flying wing type configuration, which is designed to be susceptible to Body Freedom Flutter due to low pitch inertia. In the third Aeroelastic Prediction Workshop lead by NASA, this UAV is the subject of investigation to do research within the Flight Test working group, in order to consolidate the tools used by each partner in the workshop, learn more about active flutter suppression, and share knowledge and experiences within the workshop. The Finite Element Model together with the outer mold line of the X-56 is used as provided by AFRL. Two level of fidelity analyses have been performed; a flutter analyses based on the Doublet Lattice Method as included in the commercial software ZAERO as well as the flutter analyses based on the Computational Fluid Dynamic analyses using the inhouse flow solver ENFLOW. The paper will describe and share the results for future comparison with the Aeroelastic Prediction Workshop.

This article describes the challenges of integrating smart sensing, actuation, and control concepts into an over-sensed and over-actuated technology integrator. This technology integrator has more control inputs than the expected responses or outputs (over-actuated), and its every state is measured using more than one sensor system (over-sensed). The hardware integration platform is chosen to be a wind tunnel model of a low-speed aircraft wing such that it can be tested in a large university-level wind tunnel. This hardware technology integrator is designed for multiple objectives. The nature of these objectives is aerodynamic, structural, and aeroelastic, or, more specifically; drag reduction, static and dynamics loads control, aeroelastic stability control, and lift control. Enabling technologies, such as morphing, piezoelectric actuation and sensing, and fibre-optic sensing are selected to fulfil the mentioned objectives. The technology integration challenges are morphing, actuation integration, sensor integration, software and data integration, and control system integration. The built demonstrator shows the intended level of technology integration.

This paper deals with the simultaneous gust and maneuver load alleviation problem of a seamless active morphing wing. The incremental nonlinear dynamic inversion with quadratic programming control allocation and virtual shape functions (denoted as INDI-QP-V) is proposed to fulfill this goal. The designed control allocator provides an optimal solution while satisfying actuator position constraints, rate constraints, and relative position constraints. Virtual shape functions ensure the smoothness of the morphing wing at every moment. In the presence of model uncertainties, external disturbances, and control allocation errors, the closed-loop stability is guaranteed in the Lyapunov sense. Wind tunnel tests demonstrate that INDI-QP-V can make the seamless wing morph actively to resist “1-cos” gusts and modify the spanwise lift distribution at the same time. The wing root shear force and bending moment have been alleviated by more than 44% despite unexpected actuator fault and nonlinear backlash. Moreover, during the experiment, all the input constraints were satisfied, the wing shape was smooth all the time, and the control law was executed in real time. Furthermore, as compared with the linear quadratic Gaussian control, the hardware implementation of INDI-QP-V is easier; the robust performance of INDI-QP-V is also superior.