Steel and Composite Structures

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A robust multi-objective localized outrigger layout assessment model under variable connecting control node and space deposition

  • Lee, Dongkyu (Department of Architectural Engineering, Sejong University) ;
  • Lee, Jaehong (Department of Architectural Engineering, Sejong University) ;
  • Kang, Joowon (School of Architecture, Yeungnam University)
  • Received : 2018.11.06
  • Accepted : 2019.11.05
  • Published : 2019.12.25
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Abstract

In this article, a simple and robust multi-objective assessment method to control design angles and node positions connected among steel outrigger truss members is proposed to approve both structural safety and economical cost. For given outrigger member layouts, the present method utilizes general-purpose prototypes of outrigger members, having resistance to withstand lateral load effects directly applied to tall buildings, which conform to variable connecting node and design space deposition. Outrigger layouts are set into several initial design conditions of height to width of an arbitrary given design space, i.e., variable design space. And then they are assessed in terms of a proposed multi-objective function optimizing both minimal total displacement and material quantity subjected to design impact factor indicating the importance of objectives. To evaluate the proposed multi-objective function, an analysis model uses a modified Maxwell-Mohr method, and an optimization model is defined by a ground structure assuming arbitrary discrete straight members. It provides a new robust assessment model from a local design point of view, as it may produce specific optimal prototypes of outrigger layouts corresponding to arbitrary height and width ratio of design space. Numerical examples verify the validity and robustness of the present assessment method for controlling prototypes of outrigger truss members considering a multi-objective optimization achieving structural safety and material cost.

Keywords

Acknowledgement

Supported by : NRF (National Research Foundation of Korea)

This research was supported by a grant (NRF2017R1A4A1015660) from NRF (National Research Foundation of Korea) funded by MEST (Ministry of Education and Science Technology) of Korean government. This work was also supported by LG Yonam Foundation (of Korea).

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