A Flexible Methodology for Analysis and Optimization of Unconventional Wing Structural Geometries Using a Computationally Efficient Aeroelastic Model
Author(s)
Solano Sarmiento, Heriberto David
Advisor(s)
Editor(s)
Collections
Supplementary to:
Permanent Link
Abstract
Aerospace research and industry have been focused on pushing boundaries and designing next-generation aircraft to meet the needs of the aviation sector and reducing its impact on climate change. During the early stages of design, it is important to design the structure to sustain loads specified by 14-CFR regulatory authorities while keeping the weight, sizes, and costs low. Unconventional designs, such as the Truss-Braced Wing (TBW) design and the Parallel Electric-Gas Utilization Scheme (PEGASUS), promise great structural and aerodynamic efficiency but require additional dynamic load considerations, and more accurate physical structural models. This work centers around the design and optimization of unconventional wing structures. A methodology is developed to best decide which model fidelity and tools to use during design space exploration to maximize exploration performance, with respect to the number of configurations considered, inter-model bias and correlation, and confidence of optimum. In addition, a multi-engine configuration structural model will be developed and tested to assess the ability of the lower-fidelity part of the methodology to assess different wing layout configurations based on diverse sets of structural constraints, as well as rib mass surrogate models to further improve its accuracy and lower its biases.
For applications where high-fidelity models are not convenient, a process is developed that enables the inclusion of pre-trained stress field surrogates to better represent the stress of the structure when a beam model is used. Furthermore, a computationally efficient model of the truss-braced concept is developed, which has multiple components joined to one another as the primary structure. The model will be shown to have well-conditioned low-order physics, allow for dynamic loads, and have an improved fidelity thanks to the inclusion of strength and buckling considerations for all the individual structural components.
To test the methodology, five sets of experiments will be carried out: 1) demonstrate the methodology of choosing appropriate model fidelity by tracking the number of feasible alternatives explored and fitness of solution tracked; 2) demonstrate the accuracy of the developed lower-fidelity model by comparing to a higher-fidelity model with regards to structure layout sizing; 3) demonstrate that by adding stress surrogates from a higher-fidelity source into a lower-fidelity model, it is possible to increase the amount of accurate information at early stages of design and aid in structural sizing; 4) demonstrate that the lower-fidelity model can properly analyze and size a complex multi-member structure; 5) demonstrate that the developed conditioning procedure lowers the condition number of the differential-algebraic equation system and improves its run-time, under varying conditions.
Finally, the capabilities developed will be demonstrated to perform a study on the effects of engine placement and layout when addressing gust loads on the PEGASUS configuration, as well as a design space exploration of the TBW, with regards to key design variables for the structural assessment of novel configurations such as airfoil thickness, structural joint locations, and rib spacing, in both static and dynamic scenarios, with the dynamic scenarios looking at the strut placement as the main variable of interest. The resulting methodology provides a multi-fidelity, fully modular, and flexible approach for the analysis and sizing of unconventional wing structural designs at the conceptual phase, allowing designers to assess potential strengths and pitfalls of different layouts and configurations before committing to more computationally expensive efforts in the latter stages of design.
Sponsor
Date
2023-05-19
Extent
Resource Type
Text
Resource Subtype
Dissertation