Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/29156
Title: Mass Optimization of Crane Box Girder Considering Both Ribs and Diaphragms using APDL
Authors: Ren, Y
Liu, X
Wang, B
Keywords: mass optimization;lightweight;crane girder;ribs;diaphragms;APDL
Issue Date: 10-May-2024
Publisher: Springer Nature
Citation: Ren, Y., Liu, X. and Wang, B. (2024) 'Mass Optimization of Crane Box Girder Considering Both Ribs and Diaphragms using APDL', International Journal of Steel Structures, 24, , pp. 672 - 692. doi: 10.1007/s13296-024-00846-3.
Abstract: Mass optimization of crane box girder considering both ribs and diaphragms is a crucial aspect of crane structural design in mechanical engineering. However, two common challenges often obscure this process: the sizing of stiffeners such as diaphragms and ribs, and the selection of constraints on state variables related to stresses and deformations for various load cases. In response, this paper focuses on optimizing the dimensions, number, and placement of stiffeners, including ribs and diaphragms, in a two-girder overhead crane structure. The paper begins by establishing criteria for the initial height of the box girder through a comparative analysis of structural strength and stiffness. Subsequently, dimensional relationships between stiffeners and the girder section are built in accordance with the principles of local plate stability. Following this, the ANSYS Parametric Design Language (APDL) program is coded and executed to optimize the crane mass using three methods: sub-problem approximation, sweep, and first-order methods via Module Design OPT for four chosen sets of state variables. A comparative analysis of the optimum crane mass, based on the rounded-up design variables, reveals that constraints on stresses and deformations from both vertical and transversal impact cases, as well as the vertical frequency from dynamic vibration cases, yield the best results. Furthermore, the proposed APDL method is compared and validated against Grey Wolf Optimizer, Whale Optimization Algorithm, Particle Swarm Optimization, and Genetic Algorithm. Finally, a parametric study is conducted using curves and tables to explore the influence of structural stiffness and material property on the optimized dimensions of the girder and stiffeners, as well as the overall mass and mechanical performance.
URI: https://bura.brunel.ac.uk/handle/2438/29156
DOI: https://doi.org/10.1007/s13296-024-00846-3
ISSN: 1598-2351
Other Identifiers: ORCiD: Bin Wang https://orcid.org/0000-0002-1398-6599
Appears in Collections:Dept of Civil and Environmental Engineering Embargoed Research Papers

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