Defining structural robustness under seismic and simultaneous actions: an application to precast RC buildings

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• 作者：Domenico Asprone ; Raffaele De Risi ; Gaetano Manfredi
• 关键词：Structural robustness ; Robustness quantification ; Extreme events ; Industrial buildings
• 刊名：Bulletin of Earthquake Engineering
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：14
• 期：2
• 页码：485-499
• 全文大小：808 KB
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• 作者单位：Domenico Asprone (1)
  Raffaele De Risi (1)
  Gaetano Manfredi (1)
  
  1. Department of Structures for Engineering and Architecture, University of Naples Federico II, Naples, Italy
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Geotechnical Engineering
  Civil Engineering
  Geophysics and Geodesy
  Hydrogeology
  Structural Geology
  
• 出版者：Springer Netherlands
• ISSN：1573-1456

文摘

The increasing complexity of urban systems is making robustness a crucial requirement for structural design. The paper deals with the concept of robustness of civil structures against extreme events. After a brief literature survey, a novel point of view to robustness assessment is proposed, fitting the most accepted robustness definition. The proposed approach is discussed and compared with other methodologies for quantifying structural robustness. Thus, the methodology is developed and applied to an existing precast industrial building case study, assumed to be prone to seismic and wind hazards. In particular, the case study is assumed to be located in Emilia, Italy, where a significant earthquake occurred in 2012, causing relevant damage to gravity load designed industrial buildings. Three structural options are discussed, namely a simple supported beam–column connection (gravity load designed solution) and two pinned connections (seismic designed solution), where only one of them satisfies the current structural code requirements. The results are discussed in terms of robustness quantification, by means of a robustness matrix. The authors envisage that this approach can be effectively adopted for portfolios of existing structures, to prioritize retrofitting interventions, aimed at maximizing the overall risk mitigation with limited economic resources.