Back to Search
Start Over
A new stress-based topology optimization approach for finding flexible structures
- Source :
- Structural and Multidisciplinary Optimization. 64:1997-2007
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- This paper presents a new FE-based stress-related topology optimization approach for finding bending governed flexible designs. Thereby, the knowledge about an output displacement or force as well as the detailed mounting position is not necessary for the application. The newly developed objective function makes use of the varying stress distribution in the cross section of flexible structures. Hence, each element of the design space must be evaluated with respect to its stress state. Therefore, the method prefers elements experiencing a bending or shear load over elements which are mainly subjected to membrane stresses. In order to determine the stress state of the elements, we use the principal stresses at the Gauss points. For demonstrating the feasibility of the new topology optimization approach, three academic examples are presented and discussed. As a result, the developed sensitivity-based algorithm is able to find usable flexible design concepts with a nearly discrete 0 − 1 density distribution for these examples.
- Subjects :
- Control and Optimization
Computer science
Topology optimization
0211 other engineering and technologies
02 engineering and technology
Bending
Topology
Computer Graphics and Computer-Aided Design
Displacement (vector)
Computer Science Applications
Stress (mechanics)
020303 mechanical engineering & transports
0203 mechanical engineering
Conceptual design
Control and Systems Engineering
Position (vector)
Sensitivity (control systems)
Engineering design process
Software
021106 design practice & management
Subjects
Details
- ISSN :
- 16151488 and 1615147X
- Volume :
- 64
- Database :
- OpenAIRE
- Journal :
- Structural and Multidisciplinary Optimization
- Accession number :
- edsair.doi...........c1e78a48349603abe3a5ef9bbf8aca50