Skip to main content

A short description of your project

Project description

TCRA

Tropical Cyclone Risk Analysis [TCRA] The documentation of this tool is published here: TCRA documentation

Overview

Tropical Cyclone Risk Analysis (TCRA) is a Python package that allows for the development of scenario-based tropical cyclone risk analysis of buildings and Electrical Power Network (EPN). This tool performs scenario-hazard analysis based on historical or simulated cyclone tracks, fragility-based damage analysis, damage ratio analysis, loss estimation, recovery simulation of damaged structures, and social impact assessments on the community. It also enables decision-makers to make rehabilitation decisions and perform rehabilitation scenario analysis.

Dependency

  • warnings
  • numpy
  • pandas
  • matplotlib
  • scipy
  • folium
  • collections
  • typing

Version Reslease

  • v 0.0.1 : July, 2024 The current version is a ongoing research project, which is still a pre-release.

Authors

Funding Statement

  • This tool development is partly supported by the Coalition for Disaster Resilient Infrastructure (CDRI) fellowship 2023-24 Cohort under the Project titled "Community Disaster Resilience Assessment by Integrating Functionality of Buildings and Critical Infrastructure Systems". The development of this tool is not necessarily expressed the view of the CDRI.

Project Team

  1. Principal Investigator: Ram Krishna Mazumder, Asset Management Consultant, Arcadis U.S. Inc.
  2. Co-Principal Investigator: Subhrajit Dutta, Assistant Professor, Department of Civil Engineering, National Institute of Technology Silchar, Assam, India
  3. Co-Principal Investigator: Sohel Rana, Research Lecturer, Institute of Earthquake Engineering Research, Chittagong University of Engineering & Technology, Bangladesh.
  4. Research Assistant: Swaranjit Roy, IEER, Chittagong University of Engineering & Technology, Bangladesh.
  5. Research Assistant: Sahil Chettri, Department of Civil Engineering, NIT Silchar, Assam, India

Citing TCRA

Source Files

Github: https://github.com/rxm562/TCRA.git Documentation: https://tcra.readthedocs.io

License

The project is licensed under the MIT license. See the LICENSE file

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bogs-0.1.9.tar.gz (16.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

bogs-0.1.9-py3-none-any.whl (19.6 kB view details)

Uploaded Python 3

File details

Details for the file bogs-0.1.9.tar.gz.

File metadata

  • Download URL: bogs-0.1.9.tar.gz
  • Upload date:
  • Size: 16.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.13.1

File hashes

Hashes for bogs-0.1.9.tar.gz
Algorithm Hash digest
SHA256 b0ea4111093d8aa124d1ed6e0411587d4a5589b23bd8ec5e5f7589a545827029
MD5 9c5246b88adf9a9c046bf3fa305c0e84
BLAKE2b-256 0e8d6566b9419a2c73fcec91e4d1e3459dab3647829603840d1881138348f03d

See more details on using hashes here.

File details

Details for the file bogs-0.1.9-py3-none-any.whl.

File metadata

  • Download URL: bogs-0.1.9-py3-none-any.whl
  • Upload date:
  • Size: 19.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.13.1

File hashes

Hashes for bogs-0.1.9-py3-none-any.whl
Algorithm Hash digest
SHA256 3d24d0da39bba55d8a299378dfe980f1044b5c2ba4b87a5e2c6b6972d3566f4d
MD5 312e3864122baff4f6449a00250b1fc6
BLAKE2b-256 915ab9bb246433b6d079ff0210a50ed47282a5c15064e0a480b2a42d0cab8076

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page