Residual behaviour and damage assessment of UHPC-filled double-skin steel tubular columns after lateral impact

• The post-impact behaviour of UHPC-filled DST column was experimentally and numerically investigated. • The impact resistant mechanism of UHPC-filled DST columns with different impact heights was investigated. • Damage indexes that can consider the influences of both global and local deflections were proposed. • Two types of machine learning prediction models were proposed for the damage assessment of impacted UHPC-filled DST columns. Ultra-high performance concrete (UHPC)-filled double-skin steel tubular (DST) column has great potential to be used in the protective structures. Although its lateral impact behaviour has been well understood, the residual behaviour after lateral impact remains unexplored. As a result, this study extensively investigated the residual behaviour and damage assessment of UHPC-filled DST columns after lateral impact. Firstly, a set of six DST columns were designed and tested under lateral impact, followed by static axial compression. In addition, two intact columns were subjected to static axial compression for comparative analysis. Secondly, the refined finite element models were developed and validated using the current test data, and the impact resistant mechanism of UHPC-filled DST columns with different impact locations was analysed. Thirdly, the suitability of different damage indexes for the damage assessment of impacted UHPC-filled DST columns was evaluated. Two damage indexes, the ratio of mid-height deflection to column height ( R 1 ), and the ratio of local deflection to the column diameter ( R 2 ), were proposed for the DST columns. Finally, two types of machine learning-based models were developed to predict the impact damage of UHPC-filled DST columns. The prediction models were interpreted locally and globally using the additive feature attribution method Shapley Additive Explanation (SHAP). The machine learning-based prediction models can rapidly evaluate the damage extent of impacted UHPC-filled DST column, which hold great significance for the selection of strengthening and retrofitting schemes.

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Publication Details

Journal
Thin-Walled Structures
Published
2024-10-19
DOI
https://doi.org/10.1016/j.tws.2024.112602
Citations
10
Primary Topic
Structural Behavior of Reinforced Concrete
Type
article
Field-Weighted Citation Impact
2.65
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article

Residual behaviour and damage assessment of UHPC-filled double-skin steel tubular columns after lateral impact

Ziming Xiong, Chengqing Wu, Weiqiang Wang, Da Chen et al.
10 citations
Thin-Walled Structures
Structural Behavior of Reinforced Concrete
2.65
article

Residual behaviour and damage assessment of UHPC-filled double-skin steel tubular columns after lateral impact

Ziming Xiong, Chengqing Wu, Weiqiang Wang, Da Chen, Yang Yu
article en
10 citations

Abstract

• The post-impact behaviour of UHPC-filled DST column was experimentally and numerically investigated. • The impact resistant mechanism of UHPC-filled DST columns with different impact heights was investigated. • Damage indexes that can consider the influences of both global and local deflections were proposed. • Two types of machine learning prediction models were proposed for the damage assessment of impacted UHPC-filled DST columns. Ultra-high performance concrete (UHPC)-filled double-skin steel tubular (DST) column has great potential to be used in the protective structures. Although its lateral impact behaviour has been well understood, the residual behaviour after lateral impact remains unexplored. As a result, this study extensively investigated the residual behaviour and damage assessment of UHPC-filled DST columns after lateral impact. Firstly, a set of six DST columns were designed and tested under lateral impact, followed by static axial compression. In addition, two intact columns were subjected to static axial compression for comparative analysis. Secondly, the refined finite element models were developed and validated using the current test data, and the impact resistant mechanism of UHPC-filled DST columns with different impact locations was analysed. Thirdly, the suitability of different damage indexes for the damage assessment of impacted UHPC-filled DST columns was evaluated. Two damage indexes, the ratio of mid-height deflection to column height ( R 1 ), and the ratio of local deflection to the column diameter ( R 2 ), were proposed for the DST columns. Finally, two types of machine learning-based models were developed to predict the impact damage of UHPC-filled DST columns. The prediction models were interpreted locally and globally using the additive feature attribution method Shapley Additive Explanation (SHAP). The machine learning-based prediction models can rapidly evaluate the damage extent of impacted UHPC-filled DST column, which hold great significance for the selection of strengthening and retrofitting schemes.

Thin-Walled StructuresVol. 205
University of Technology Sydney (AU), Hohai University (CN), UNSW Sydney (AU)
Sustainable cities and communities
Openalex Percentile: Top 11%
Structural Behavior of Reinforced Concrete
2.65
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