A robust design of an innovative shaped rebar system using a novel uncertainty model

Aldoumani, Nada; Haddad Khodaparast, Hamed; Giannetti, Cinzia; Abdallah, Zakaria; Cameron, Ian M; Friswell, Michael I; Sienz, Johann

Abstract

The current paper has investigated a newly developed re-bar system by implementing uncertainty models to optimise its geometry. The study of the design parameters of this re-bar system has been carried out utilising a novel uncertainty model that has been developed at Swansea University. The importance of this invention comes from the fact that the whole process of optimisation has been automated by linking ANSYS Workbench to MATLAB via the in-house written code, Despite the fact that in the past, ANSYS APDL was linked to MATLAB, however, the APDL was very limited to only simple geometries and boundary conditions unlike the Workbench which can simulate complex features. These shortfalls have been overcome by automating the process of optimisation, identifying the key influential parameters and the possibility to carry out a huge number of trials. Moreover, the tools that have been developed can pave the way for robust optimisation of this proposed structure. The uncertainty in the design parameters of this re-bar system is of a paramount importance in order to optimise the bond strength between the newly developed rebar and the concrete matrix as well as to fully understand the behaviour of the proposed system under pull-out conditions. The interface between the rebar and the concrete matrix was considered as a ‘cohesive zone’ whereby the interfacial area is studied as a function of the bonding strength.

Citation

Aldoumani, N., Haddad Khodaparast, H., Giannetti, C., Abdallah, Z., Cameron, I. M., Friswell, M. I., & Sienz, J. (2018). A robust design of an innovative shaped rebar system using a novel uncertainty model. Structural and Multidisciplinary Optimization, 58(4), 1351-1365. https://doi.org/10.1007/s00158-018-2050-z

• Journal Article Type: Article
• Acceptance Date: Jul 10, 2018
• Online Publication Date: Aug 17, 2018
• Publication Date: Oct 31, 2018
• Deposit Date: Jul 11, 2023
• Publicly Available Date: Jul 11, 2023
• Journal: Structural and Multidisciplinary Optimization
• Print ISSN: 1615-147X
• Electronic ISSN: 1615-1488
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 58
• Issue: 4
• Pages: 1351-1365
• DOI: https://doi.org/10.1007/s00158-018-2050-z
• Public URL: https://uwe-repository.worktribe.com/output/10910348