This repository is used to store jupyter notebooks that rely on the IN-CORE (pyincore) modeling framework.
This notebook is used to demonstrate pyincore's multi-hazard damage capabilities. Computes building economic losses, risks, and building failure. Uses seismic-tsunami hazard at Seaside, Oregon as a testbed community. Demonstrates a variety of plotting methods including interactive spatial maps. Last updated using pyIncore 0.5.2.
A Spatial Bayesian Network (SBN) is constructed and implemented in a jupyter notebook. The notebook acts as an interface for the SBN. The user specifies input in two files corresponding to community and parcel level decisions. The notebook runs the SBN and the user can view the results spatially in interactive maps.
The notebook here uses pyincore to damage the infrastructure at Seaside. This notebook is continually updated. There is a secondary notebook that estimates repair times for building infrastructure using HAZUS restoration curves. Last updated using pyIncore 0.9.2.
The work in this directory employs an optimization routine to determine mitigation strateiges for buildings in Seaside. The damage analysis is performed using pyIncore. This work was performed by Tarun and Dylan. Last updated using pyIncore 0.9.2
This notebook is an updated of the Seaside notebook on the pyIncore website. It follows the IN-CORE flowchart up to restoration of physical infrastructure. Multiple people have contributed to this.
Notebook provided by Mehrshad to use the Seaside CGE model.
Notebook used to create "how-to" in-core video. This notebook demonstrates pyincore's building damage abilities for earthquake and tsunami damage.