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Multi-Material Topology Optimization as a Concept Generation and Design Tool Queen's University

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Vierhout, Vierhout, author.
Contributor:
Kim, Il Yong
Li, Daozhong
Pamwar, Manish
Roper, Stephen
Sangha, Balbir
Conference Name:
WCX SAE World Congress Experience (2019-04-09 : Detroit, Michigan, United States)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2019
Summary:
AbstractConventional vehicle design is continually being pushed by consumers and regulations to reach higher level of fuel efficiency and system performance. New methods such as use of alternative structural materials and structural optimization are being utilized heavily in the automotive industry. Currently, materials such as advanced composites, polymers, aluminum and magnesium are all being considered as candidates for alternatives to conventional steel parts to help meet lightweight performance targets.While topology optimization has proven to be a powerful in many case studies for automotive light weighting studies, it is currently constrained for use with one material in the optimization algorithm. Multi-material topology optimization (MMTO) methods presented in this paper demonstrate the tools capability to optimize material selection simultaneously alongside material layout for a given design space and desired weight target. Extensions to MMTO methodology demonstrate the ability to manipulate the mathematical problem statement for optimization in order to achieve a desired amount of each material in the final solution.Discussed in this paper is the application of MMTO to an automotive case study and the examination of the computational solutions obtained from 2-material optimization. First, the optimal material selection and layout is presented and analyzed as the multi-material optimum for the given weight target. Next, the optimization problem statement is manipulated to predetermine the amount of steel and aluminum by volume in the final computational solution. The results are compared quantitatively for stiffness performance against the true optimal solution. Last, material existence and placement trends are discussed for the set of optimization results as well as the varying levels of performance for different abstract cost levels in each solution
Notes:
Vendor supplied data
Publisher Number:
2019-01-1095
Access Restriction:
Restricted for use by site license

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