1 option
Frequency-Constrained Multi-Material Topology Optimization: Commercial Solver Integrable Sensitivities Queen's University
- Format:
- Book
- Conference/Event
- Author/Creator:
- Huang, Yuhao, author.
- Conference Name:
- WCX SAE World Congress Experience (2023-04-18 : Detroit, Michigan, United States)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2023
- Summary:
- Numerical tools such as topology optimization (TO) have seen large development in both academic and industrial settings, enabling the optimization of structural objectives and/or attributes, subject to a wide range of constraints, pertinent to the engineering and design problems of automotive and aerospace industries. Classical TO methods assume the use of a single material (SMTO), however, a recent and important advancement in this field is that of multi-material topology optimization (MMTO), capable of simultaneous material existence and selection optimization. This is of heightened importance in the aforementioned industries, where many costly engineering materials can be used, but their selection is delegated to engineer experience. Consideration of modal characteristics (id est, natural frequencies) in MMTO efforts have seen marginal development in recent years, yet is vital to both industries, who's products are each subject to uncontrolled environments and vibratory motion. Where frequency has been considered in MMTO, mathematical frameworks require the usage of model attributes that are not extractable from commercial finite element analysis (FEA) solvers, leading to reduced computational efficiency. This paper presents an advancement of the frequency-constrained MMTO sensitivities previously utilized in SMTO, enabling the use of commercial solvers, thus inheriting computational improvements. A derivation of sensitivities, a detailed discussion, and analysis of two case studies have been included, so as to provide the reader with a sound understanding of the nature of the constraint sensitivities, and how they may be able to intuit results
- Notes:
- Vendor supplied data
- Publisher Number:
- 2023-01-0029
- Access Restriction:
- Restricted for use by site license
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.