Dynamic Aeroelastic Performance Optimization of Adaptive Aerospace Structures Employing Structural Geometric Nonlinearities
Notice bibliographique
Résumé
This thesis proposes a framework for the design optimization of geometric nonlinearities developed by active elements embedded in truss-like aerospace structures for the purpose of attenuating their dynamic aeroelastic response under turbulent aerodynamic gust conditions.Dynamic aeroelastic responses are analyzed considering random Power Spectral Density (PSD) and Tuned Discrete Gust (TDG) excitation profiles.MSC NASTRAN® is employed for the development of the dynamic aeroelastic models where the random PSD with a continuous Davenport spectrum (DS) and the TDG with a One-minus cosine (OMC) wind gust excitation profiles are developed.This work presents a multi-objective genetic optimization algorithm (MOGA) utilized to determine optimal prestress values through active element actuations for the purpose of tuning the geometric stiffness and therefore modal response of the structure when exposed to gust excitations.Additionally, this work contributes a new simplified control metric for comparing active member locations.Two case studies are presented to minimize the pointing error of both a simplified and high-fidelity (HF) Earth-based very-long baseline interferometry (VLBI) antenna structure.The pointing error is calculated as the spatial displacement of the secondary reflector using time-consistent displacements (TCD) imparted by time consistent loads (TCL).To increase the computational efficiency of the design optimization process of the HF model, model order reduction is conducted using the Craig-Bampton method which resulted in the computation time decreasing from 39.21 minutes to only 50 seconds while maintaining a 99.9% Modal Assurance Criterion (MAC) correlation in the first 20 mode shapes of interest of the structure.With the reduced model, the framework used multi-objective genetic optimization with iii the dual objectives of decreasing total pointing error while minimizing the total strain energy in the system as a result of both the applied aerodynamic and inertia loads as well as the applied actuations.The yield strength of the elements and their maximum displacements were used as design constraints to ensure integrity of the structure.Pareto fronts are presented containing optimal responses for 16, 32, and 44 active members of the structure.The utopian point method was employed to calculate the best configuration of active members to be considered.A reduction of 82.6% with a total strain energy increase of 292.5% was obtained for the primary operating case under PSD gust excitation.On the other hand, at the increased mean wind speeds of the secondary operating case, the developed design algorithm was able to reduce the total pointing error by 80.9% but with a total strain energy increase of 825.3%.Similarly, for TDG analysis with the OMC excitation profile the optimization algorithm reduced the total pointing error by 51.6% with a TSE increase of 2098.1% and 80.5% with a TSE increase of 48.7% for the primary and secondary operating conditions, respectively, when compared to the uncontrolled response.The adaptive nature of the presented methodology allows a single actuator layout to mitigate structural response for a variety of load cases, which is a large benefit over many traditionally passive techniques.This thesis expands the existing usage of geometric nonlinearities to determine optimal active element location and actuations for given optimization objectives under realistic environmental loading conditions.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».