An BESO Approach for Optimal Retrofit Design of Steel Rectangular-Hollow-Section Columns Supporting Crane Loads
Author(s): |
Rut Su
Sawekchai Tangaramvong Thu Huynh Van |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 14 February 2023, n. 2, v. 13 |
Page(s): | 328 |
DOI: | 10.3390/buildings13020328 |
Abstract: |
In this paper, we propose a cost-effective optimal-topology retrofitting technique for hollow-steel-section columns to sufficiently support industrial running cranes. A so-called bi-directional evolutionary structural optimization (BESO) method was encoded within the MATLAB modeling framework, with a direct interface with an ANSYS commercial finite-element analysis program, to determine the optimal topology of double external steel plates connected to columns in a 3D space. For the initial ground structure, we have adopted standard uniform double U-shaped external stiffener plates located at the top and bottom flange layers of an I-beam to box-column connection (IBBC) area. The influences of inelastic materials and the incorporated nonlinear geometry can effectively describe the premature (local buckling) failures of the columns in an IBBC area. The applications of the proposed optimal-topology BESO-based stiffening method are illustrated through the retrofitting of three hollow-steel-section columns, characterized by non-slender and slender compression sections. Some concluding remarks are provided on the pre- and post-retrofitted responses of the columns, with the results showing both the accuracy and robustness of the proposed external stiffening schemes. |
Copyright: | © 2023 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10712638 - Published on:
21/03/2023 - Last updated on:
10/05/2023