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https://github.com/friesischscott/uncertaintyquantification.jl

Uncertainty Quantification in Julia
https://github.com/friesischscott/uncertaintyquantification.jl

hacktoberfest julia metamodeling monte-carlo-simulation reliability-analysis sensitivity-analysis uncertainty-quantification

Last synced: 8 days ago
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Uncertainty Quantification in Julia

Host: GitHub
URL: https://github.com/friesischscott/uncertaintyquantification.jl
Owner: FriesischScott
License: mit
Created: 2019-06-30T13:49:45.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2024-11-05T10:20:46.000Z (9 days ago)
Last Synced: 2024-11-05T10:39:52.932Z (9 days ago)
Topics: hacktoberfest, julia, metamodeling, monte-carlo-simulation, reliability-analysis, sensitivity-analysis, uncertainty-quantification
Language: Julia
Homepage:
Size: 20.5 MB
Stars: 31
Watchers: 5
Forks: 11
Open Issues: 34
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        UncertaintyQuantification.jl

============================

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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3993816.svg)](https://doi.org/10.5281/zenodo.3993816)

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[![](https://img.shields.io/badge/docs-dev-blue.svg)](https://friesischscott.github.io/UncertaintyQuantification.jl/dev)

A Julia package for uncertainty quantification. Current functionality includes:

* Simulation-based reliability analysis

  * Monte Carlo simulation

  * Quasi Monte Carlo simulation (Sobol, Halton, Latin Hypercube, Lattice Rule)

  * Line Sampling

  * Subset Simulation

* Sensitivity analysis

  * Gradients

  * Sobol indices

* Metamodeling

  * Polyharmonic splines

  * Polynomial Chaos Expansion

  * Response Surface Methodology

* Third-party solvers

  * Connect to any solver by injecting random samples into source files

  * HPC interfacing with slurm