Search arXiv⌕ Search

arXiv · 2603.19725

Nonlinear Flexibility Effects on Flight Dynamics of High-Aspect-Ratio Wings

Abstract

This paper investigates the effects of geometric nonlinearity and structural flexibility on the flight dynamics of high-aspect-ratio wings representative of high-altitude long endurance aircraft configurations. A coupled aeroelastic flight dynamic framework is developed, combining a geometrically exact beam formulation for the structure, unsteady two-dimensional strip theory for the aerodynamics, and quaternion-based rigid-body equations for the flight dynamics. The three subsystems are monolithically coupled through consistent load and motion transfer at each time step. A systematic parametric study is conducted by varying the wing stiffness across several orders of magnitude, spanning from nearly rigid to very flexible configurations. The study reveals that increasing flexibility fundamentally alters trim conditions, flutter boundaries, and dynamic gust response. In particular, large static deformations create an effective dihedral that modifies the lift direction and necessitates higher trim angles of attack. The phugoid mode is shown to destabilise at high flexibility levels, consistent with findings in the literature. Flutter speed degradation is quantified as a function of the stiffness parameter, showing significant reductions for very flexible configurations when the pre-stressed equilibrium is correctly accounted for. The framework is validated against published aircraft benchmarks, demonstrating good agreement in natural frequencies, flutter speeds, and nonlinear static deflections. Results provide quantitative guidance on when linear analysis is acceptable and when fully coupled nonlinear tools become essential.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Nikolaos D. Tantaroudas, Ilias Karachalios. 2026-04-14. Nonlinear Flexibility Effects on Flight Dynamics of High-Aspect-Ratio Wings. https://arxiv.org/abs/2603.19725

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Centering Drives Normalization Gains: Price-Offset Nuisances in Cross-Sectional Return Prediction

Cross-sectional return prediction from raw intraday bars is sensitive to each instrument price level, an additive nuisance under a return-ranking hypothesis. We test whether removing this offset, rather than rescaling amplitudes or changing the encoder, explains gains on a point-in-time CSI~300 five-minute panel. We evaluate eight parameter-matched encoders with and without RevIN normalization; a parameter-free ladder then separates identity, scale-only, centering, last-value referencing, differencing, and standardization across all fields and restricted channels. Centering drives the reliable effect, while scale-only normalization does not help. All eight paired effects are positive and survive Holm correction on raw rank IC, after style residualization, and after further residualizing on short-term reversal. Among six stronger encoders, gains of 0.0376-0.0567 exceed the 0.0109 spread of normalized IC (0.0830-0.0939). Price-only standardization retains 93--101% of the all-field gain. These results place the main effect in transformed price-channel offset removal rather than amplitude scaling or encoder choice.

cs.CE↗

TERRA-NG v1.0: Extreme-Scale, GPU-accelerated Mantle Convection

We present TERRA-NG, a portable, GPU-accelerated, matrix-free mantle-convection code. A single Kokkos C++ implementation runs at scale on NVIDIA, AMD, and Intel GPU supercomputers. TERRA-NG has a deliberately narrow design: built on a radially extruded mesh of spherical wedges, tailored to the spherical shell geometry, which enables domain-specific optimizations like single quadrature-point integral-evaluations, radial coordinate storage compression and radial shared-memory tiling. The corresponding low-order $W_1$-iso-$W_2/W_1$ wedge-based Stokes--energy discretisation is verified against the Zhong et al.(2008) spherical-shell convection benchmark suite. We showcase TERRA-NG through strong- and weak-scaling on the JUWELS Booster (NVIDIA A100), MareNostrum 5 (NVIDIA H100), LUMI-G (AMD MI250X), Hunter (AMD MI300A APU), and SuperMUC-NG Phase 2 (Intel PVC) supercomputers. Coupled mantle convection simulations at $\sim\!11$ km and $\sim\!5.6$ km radial spacing ($\sim 2.8$ B and $\sim 22$ B DoFs) can be run routinely on standard node partitions of all considered systems. Global $\sim\!1$ km-per-gridpoint mantle convection ($\sim 1.4$ T DoFs) is feasible on an extreme-scale allocation, and a sub-km hero-run at $\sim\!0.7$ km grid spacing scaling up to $\sim 11,000$ GPUs of LUMI-G ($\sim 11$ T DoFs) shows the potential of the code on future, larger machines.

cs.CE↗

AFT Neural Function Approximators for 1D Nonlinear Force Laws

Nonlinear contacts and friction strongly influence the vibration response of assembled structures, but their accurate numerical treatment is computationally demanding. The harmonic balance method is widely used to compute periodic steady-state responses, yet the required alternating frequency-time scheme becomes costly for nonsmooth and hysteretic nonlinearities and must be repeated throughout the nonlinear solution process. Here we show that this procedure can be replaced by neural networks that directly map displacement Fourier coefficients to nonlinear force coefficients and provide the corresponding Jacobian through automatic differentiation. The surrounding solver and continuation algorithms remain unchanged for the computation of frequency response curves. The neural networks exclusively learn individual nonlinear elements rather than complete system responses. Physics-based nondimensionalization and phase normalization facilitate the learning process and enable a single trained network to cover a wide range of parameter combinations. Building on the cubic spring, unilateral spring, and Jenkins elements considered here, the approach points toward a reusable library of nonlinear-element surrogates that can be combined in arbitrary number and location within a mechanical system. By bypassing the iterative force evaluation in time domain, the method offers favorable computational scaling for high-resolution analyses and systems with many nonlinear elements.

cs.CE↗