{"id":27555830,"url":"https://github.com/ma-sadeghi/poromics","last_synced_at":"2026-04-25T12:36:09.854Z","repository":{"id":284522205,"uuid":"955207373","full_name":"ma-sadeghi/poromics","owner":"ma-sadeghi","description":"A tool for rapid estimation of transport properties of 3D images of porous materials","archived":false,"fork":false,"pushed_at":"2026-04-20T21:04:44.000Z","size":3560,"stargazers_count":2,"open_issues_count":3,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2026-04-25T12:36:07.639Z","etag":null,"topics":["gpu","julia","porous-materials","porous-media","porous-media-flow","python","tortuosity","transport-phenomena"],"latest_commit_sha":null,"homepage":"https://ma-sadeghi.github.io/poromics/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ma-sadeghi.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"docs/contributing.md","funding":null,"license":"LICENSE","code_of_conduct":".github/code_of_conduct.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":"docs/roadmap.md","authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-03-26T09:26:46.000Z","updated_at":"2026-04-17T19:53:46.000Z","dependencies_parsed_at":"2025-08-23T01:20:08.146Z","dependency_job_id":"ba1a8bcb-9b5e-4e1a-a743-379f356ac80b","html_url":"https://github.com/ma-sadeghi/poromics","commit_stats":null,"previous_names":["ma-sadeghi/poromics"],"tags_count":8,"template":false,"template_full_name":null,"purl":"pkg:github/ma-sadeghi/poromics","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ma-sadeghi%2Fporomics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ma-sadeghi%2Fporomics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ma-sadeghi%2Fporomics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ma-sadeghi%2Fporomics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ma-sadeghi","download_url":"https://codeload.github.com/ma-sadeghi/poromics/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ma-sadeghi%2Fporomics/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32262801,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-25T09:15:33.318Z","status":"ssl_error","status_checked_at":"2026-04-25T09:15:31.997Z","response_time":59,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["gpu","julia","porous-materials","porous-media","porous-media-flow","python","tortuosity","transport-phenomena"],"created_at":"2025-04-19T17:55:19.094Z","updated_at":"2026-04-25T12:36:09.826Z","avatar_url":"https://github.com/ma-sadeghi.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Poromics\n\nPoromics estimates transport properties of 3D porous material images. It is GPU-accelerated and designed to be fast and easy to use.\n\n**Supported properties:**\n\n- **Tortuosity / effective diffusivity** — via Julia-based FD solver (`tortuosity_fd`) or Taichi-based LBM D3Q7 BGK solver (`tortuosity_lbm`)\n- **Absolute permeability** — via Taichi-based LBM D3Q19 MRT solver (`permeability_lbm`)\n\n## Installation\n\nThe Julia-based FD solver depends on [Tortuosity.jl](https://github.com/ma-sadeghi/Tortuosity.jl/), which is installed automatically. The LBM solvers use [Taichi](https://www.taichi-lang.org/) with automatic GPU detection.\n\n\u003e [!NOTE]\n\u003e We highly recommend using `uv` instead of `pip` to install `poromics` (or any other Python package!) as it's extremely faster. It has lots of useful features, but for all practical purposes, it is a drop-in replacement for `pip`.\n\n### Uv\n\nInstall [`uv`](https://docs.astral.sh/uv/getting-started/installation/), and then run the following command in a terminal/command prompt:\n\n```shell\nuv pip install poromics\n```\n\n### Pip\n\nIf you prefer to use `pip`, run the following command in a terminal/command prompt:\n\n```shell\npip install poromics\n```\n\n## Basic Usage\n\n\u003e [!NOTE]\n\u003e The first time you call `tortuosity_fd`, it will take a few minutes to install Julia and the required packages. This is a one-time setup. The LBM solvers (`tortuosity_lbm`, `permeability_lbm`) use Taichi and do not require Julia.\n\n### Tortuosity (Julia FD solver)\n\n```python\nimport porespy as ps\nimport poromics\n\nim = ps.generators.blobs(shape=[100, 100, 100], porosity=0.6)\nresult = poromics.tortuosity_fd(im, axis=0, rtol=1e-5, gpu=True)\nprint(result.tau, result.D_eff)\n```\n\n### Tortuosity (LBM solver)\n\n```python\nresult = poromics.tortuosity_lbm(im, axis=0, D=1e-9, voxel_size=1e-6)\nprint(result.tau, result.D_eff)\n```\n\n### Permeability (LBM solver)\n\n```python\nresult = poromics.permeability_lbm(im, axis=0, nu=1e-6, voxel_size=1e-6)\nprint(result.k)\n```\n\n### Result objects\n\n`TortuosityResult` attributes: `im`, `axis`, `porosity`, `tau`, `D_eff`, `c`, `formation_factor`, `D`.\n\n`PermeabilityResult` attributes: `im`, `axis`, `porosity`, `k`, `u_darcy`, `u_pore`, `velocity`, `pressure`.\n\n### Simulation solvers\n\nFor more control, use the solver classes directly:\n\n```python\nfrom poromics.simulation import TransientDiffusion, TransientFlow\n\nsolver = TransientDiffusion(im, axis=0, D=1e-9, voxel_size=1e-6)\nsolver.run(n_steps=100_000, tol=1e-2)\nprint(solver.concentration.shape, solver.converged)\n```\n\n## CLI\n\n\u003e [!WARNING]\n\u003e The CLI is still in development and not yet functional.\n\n```bash\nporomics --help\n```\n\n## Acknowledgments\n\nThe LBM solvers are based on [taichi_LBM3D](https://github.com/yjhp1016/taichi_LBM3D) by Yi-Jie Huang.\n\n## Roadmap\n\n- [x] Diffusional tortuosity\n    - [x] Julia FD solver ([Tortuosity.jl](https://github.com/ma-sadeghi/Tortuosity.jl/))\n    - [x] Taichi LBM D3Q7 BGK solver\n- [ ] Transient tortuosity\n    - [ ] Julia FD solver ([Tortuosity.jl](https://github.com/ma-sadeghi/Tortuosity.jl/))\n- [x] Permeability\n    - [x] Taichi LBM D3Q19 MRT solver\n- [ ] [Electrode tortuosity](https://doi.org/10.1038/s41524-020-00386-4)\n- [x] Julia/Taichi coexistence via subprocess isolation\n- [ ] Add command-line interface (CLI) for easy usage\n- [ ] Add support for [sysimage](https://julialang.github.io/PackageCompiler.jl/dev/sysimages.html) creation upon installation for faster startup\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fma-sadeghi%2Fporomics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fma-sadeghi%2Fporomics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fma-sadeghi%2Fporomics/lists"}