GithubHelp home page GithubHelp logo

shkma / lossassessment Goto Github PK

View Code? Open in Web Editor NEW
2.0 1.0 1.0 150 KB

MATLAB code to generate some results on the paper (Kitayama, & Cilsalar, 2022).

License: MIT License

MATLAB 100.00%
damage-assessment earthquake-engineering loss performance-analysis

lossassessment's Introduction

LossAssessment

This page is the online repository for the following journal article: Kitayama, S., Cilsalar, H. (2022). "Seismic loss assessment of seismically isolated buildings designed by the procedures of ASCE/SEI 7-16." Bull Earthquake Eng. https://doi.org/10.1007/s10518-021-01274-y

This repository contains seismic loss assessment MATLAB code.

Prepared by: Shoma Kitayama ([email protected]) Checked by: Huseyin Cilsalar ([email protected]) Last modified: 05.Feb.2021 Version: 2.0

#Log 28Nov2021. "README.md in main" included the title of the journal, DOI and the publications date.

16Nov2021. The manuscript was published on a journal, Bulletin of Earthquake Engineering.

05Feb2021. Three files were updated: "info_Comp_Fragility_NonStructural_Accel.m", "info_Comp_Fragility_Structural" and "info_num_Components_Structural.m".

The folder contains MATLAB codes that computes the following values that are the results of seismic loss assessment of seismically isolated buildings with SCBF designed by RI=2 and TFP-1 based on Conditional Spectra approach (notations are explained in the manuscript):

  • Loss vulnerability functions
  • Expected annual loss (EAL)
  • Expected Loss (=EL) Over Time (=t)

To implement this example code, you need to download the data of results of nonlinear seismic response analysis (i.e., multiple stripe analysis; Jalayer, 2003) from the following link:

https://drive.google.com/file/d/1pNAoIicndCVjONx4P9fMqTAlJawJbsfy/view?usp=sharing

The downloaded data (i.e., a folder, after extraction of zip file, "Response_analysis_data_CS_SCBF_RI2.0_Iso1_ASCE16") of results of seismic respone analysis should be located to the folder in the same place as the matlab files are located.

The zip file should be extracted to get a folder that contains data. The data is the results of analysis of seimically isolated building with SCBF (superstructure is designed per RI=2.0) and with the smallest required isolators (TFP-1) based on ASCE7-16 (2017) seismic design standard.

Please note that one of the MATLAB file "fn_mle_pc.m" used in this folder was obtained from the data set that is associated with the following journal article: Baker JW. (2015). “Efficient analytical fragility function fitting using dynamic structural analysis.” Earthquake Spectra, 31(1), 579-599.


Cited article that does not appear in the manuscript: Jalayer F. (2003). "Direct probabilistic seismic analysis: Implementing non-linear dynamic assessments." PhD. Thesis. Stanford University.

lossassessment's People

Contributors

shkma avatar

Stargazers

 avatar

Watchers

 avatar

Forkers

abbas-fathiazar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.