TREADS: Tool for Recovery Estimation And Downtime Simulation of buildings

Introduction

treads is a Python package to evaluate earthquake induced downtime and model recovery of buildings. This tool implements the framework presented in:

Molina Hutt, C., Vahanvaty, T. and Kourehpaz, P. (2022). “An analytical framework to assess earthquake induced downtime and model recovery of buildings.” Earthquake Spectra, 38(2): 1283-1320. https://doi.org/10.1177%2F87552930211060856

This tool is fully compatible with SimCenter’s tool for loss assessment, i.e., pelicun (https://github.com/NHERI-SimCenter/pelicun)

Requirements

treads runs under Python 3.6+. The following packages are required for it to work properly:

numpy pandas os sys more_itertools json

You can install these using pip.

Installation

treads is available at the Python Package Index (PyPI). You can simply install it using pip as follows:

pip install treads

Basic Demo

import DT_calculation 	# refer to "Example" folder

input_parameters = 'input_parameters.json'
RCtable_input = 'Repair_Class_Table.csv'
IF_delays_input = 'IF_delays_input.csv'

DMG_input = 'DMG.csv' 	# pelicun output
DL_summary_input = 'DL_summary.csv' 	# pelicun output
DV_rec_time_input = 'DV_rec_time.csv' 	# pelicun output

output_path = '**insert output directory here**'

DT_calculation.run_treads(input_parameters, RCtable_input, IF_delays_input, DMG_input, DL_summary_input, DV_rec_time_input, output_path)

Outputs

treads estimates earthquake-induced downtime to achieve Functional Recovery (FR), Re-Occupancy (RO), and Shelter-in-Place (SiP) post-earthquake recovery states for residential buildings. The following output files will be generated once you run treads:

• RC_component.csv: Component repair class matrix.
• DT_summary.csv: 10th percentile, 90th percentile, median, and mean downtime estimates.
• RS_stats.csv: Probability of a building not achieving different recovery states immediately after an earthquake.
• DT_stepfunc_xx.csv: Governing recovery trajectories to each recovery state (xx= FR, RO, SiP).
• DT_path_xx.xlsx: Recovery trajectories to each recovery state for each repair path (xx= FR, RO, SiP).
• RT_stepfunc_xx.xlsx: Repair time stepping functions for each repair sequence when each recovery state is achieved (xx= FR, RO, SiP).
• RT_RSeq_xx.csv: Repair time per story for each repair sequence when each recovery state is achieved (xx= FR, RO, SiP).
• IF_delays.csv: Impeding factor delays.

Contact

Pouria Kourehpaz, University of British Columbia, Vancouver, BC, Canada. email: pouria.kourehpaz@ubc.ca