A resilience-based framework for design optimization of interdependent buildings

Vamshi Krishna Gudipati, Eun Jeong Cha

Research output: Contribution to conferencePaper

Abstract

In performance-based design, design targets are established based on the performance needs of the buildings. However, buildings are seen in isolation and their interactions are oftentimes neglected in the design. In order to reduce the impact from future disasters, a more comprehensive planning of the built environment on a community level is needed, which should address the aspects of hazard preparedness and recovery from the disaster. Optimizing seismic designs of the inventory of buildings in a region based on community resilience would be an example of such effort. This paper intends to provide a simple and viable framework for resilience-based design optimization of interdependent buildings. Regional economic loss is used as a community-level objective in this study, where the functional interdependencies between different buildings in a community is explicitly considered. Artificial neural networks are used to approximate the seismic response of buildings for reducing the computational time in the optimization process. The framework has been illustrated with a case study of the design optimization of office and hospital buildings.

Original languageEnglish (US)
StatePublished - 2019
Event13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019 - Seoul, Korea, Republic of
Duration: May 26 2019May 30 2019

Conference

Conference13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019
CountryKorea, Republic of
CitySeoul
Period5/26/195/30/19

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Statistics and Probability

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  • Cite this

    Gudipati, V. K., & Cha, E. J. (2019). A resilience-based framework for design optimization of interdependent buildings. Paper presented at 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019, Seoul, Korea, Republic of.