{"id":15359112,"url":"https://github.com/santisoler/lapis2019","last_synced_at":"2026-02-21T16:40:52.336Z","repository":{"id":86165605,"uuid":"175065477","full_name":"santisoler/lapis2019","owner":"santisoler","description":"Poster presentation given at LAPIS 2019","archived":false,"fork":false,"pushed_at":"2019-06-07T13:24:03.000Z","size":13097,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-11-01T08:15:11.868Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"cc-by-4.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/santisoler.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-03-11T18:58:37.000Z","updated_at":"2019-06-07T13:24:01.000Z","dependencies_parsed_at":"2023-03-13T08:43:44.428Z","dependency_job_id":null,"html_url":"https://github.com/santisoler/lapis2019","commit_stats":{"total_commits":127,"total_committers":2,"mean_commits":63.5,"dds":0.007874015748031482,"last_synced_commit":"2d6dfb4c0fc953aa56c1c7eec8b1717cb6d16ce2"},"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"purl":"pkg:github/santisoler/lapis2019","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/santisoler%2Flapis2019","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/santisoler%2Flapis2019/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/santisoler%2Flapis2019/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/santisoler%2Flapis2019/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/santisoler","download_url":"https://codeload.github.com/santisoler/lapis2019/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/santisoler%2Flapis2019/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29686798,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-21T15:51:39.154Z","status":"ssl_error","status_checked_at":"2026-02-21T15:49:03.425Z","response_time":107,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: 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":[],"created_at":"2024-10-01T12:43:50.667Z","updated_at":"2026-02-21T16:40:52.289Z","avatar_url":"https://github.com/santisoler.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Gravitational fields of tesseroids with variable density\n\n[![figshare](https://img.shields.io/badge/doi-10.6084%2Fm9.figshare.8242439-blue.svg?style=flat-square)](https://doi.org/10.6084/m9.figshare.8242439)\n\n[Santiago R. Soler](https://www.github.com/santisoler)\u003csup\u003e1,2\u003c/sup\u003e,\n[Agustina Pesce](https://www.github.com/aguspesce)\u003csup\u003e1,2\u003c/sup\u003e,\nMario E. Gimenez\u003csup\u003e1,2\u003c/sup\u003e\nand\n[Leonardo Uieda](https://www.leouieda.com)\u003csup\u003e3\u003c/sup\u003e\n\n\u003e \u003csup\u003e1\u003c/sup\u003eCONICET, Argentina.\u003cbr\u003e\n\u003e \u003csup\u003e2\u003c/sup\u003eInstituto Geofísico Sismológico Volponi, Universidad Nacional de San Juan, Argentina.\u003cbr\u003e\n\u003e \u003csup\u003e3\u003c/sup\u003eDepartment of Earth Sciences, SOEST, University of Hawai'i at Mānoa, USA\u003cbr\u003e\n\nAbstract submitted to\n[LAPIS 2019: Inverse methods in Geophysics](http://lapis2019.fcaglp.unlp.edu.ar/).\n\n[![Poster](poster.jpg)](poster.pdf)\n\n## Abstract\n\nWe present a new methodology to compute the gravitational fields generated by\ntesseroids (spherical prisms) whose density varies with depth according to\nan arbitrary continuous function.\nIt approximates the gravitational fields through the Gauss-Legendre Quadrature along\nwith two discretization algorithms that automatically control its accuracy by adaptively\ndividing the tesseroid into smaller ones.\nThe first one is a preexisting two dimensional adaptive discretization algorithm that\nreduces the errors due to the distance between the tesseroid and the computation point.\nThe second is a new density-based discretization algorithm that\ndecreases the errors introduced by the variation of the density function with depth.\nThe amount of divisions made by each algorithm is indirectly controlled\nby two parameters: the distance-size ratio and the delta ratio.\nWe have obtained analytical solutions for a spherical shell with radially variable\ndensity and compared them to the results of the numerical model for linear,\nexponential, and sinusoidal density functions.\nThe heavily oscillating density functions are intended only to test the algorithm to its\nlimits and not to emulate a real world case.\nThese comparisons allowed us to obtain optimal values for the distance-size and\ndelta ratios that yield an accuracy of 0.1% of the analytical solutions.\nThe resulting optimal values of distance-size ratio for the gravitational potential and\nits gradient are 1 and 2.5, respectively.\nThe density-based discretization algorithm produces no discretizations in the linear\ndensity case, but a delta ratio of 0.1 is needed for the exponential and most sinusoidal\ndensity functions.\nThese values can be extrapolated to cover most common use cases, which are simpler than\noscillating density profiles.\nHowever, the distance-size and delta ratios can be configured by the user to increase\nthe accuracy of the results at the expense of computational speed.\nLastly, we apply this new methodology to model the Neuquén Basin, a foreland basin in\nArgentina with a maximum depth of over 5000m, using an exponential density function.\n\n\n## Notes\n\nThe poster was entirely made with Inkscape using the Glacial Indifference and Linguistics\nPor fonts, which are available under the SIL Open Font License.\n\nIf the fonts are not installed on your system, the `poster.svg` file won't look as\nexpected. Please install the needed fonts.\n\nOn `poster.pdf` the fonts have been converted to paths, so there's no need to install\nthe fonts to see `poster.pdf` correctly.\n\n## License\n\nThis work is licensed under a\n[Creative Commons Attribution 4.0 International License][cc-by].\n\n[![CC BY 4.0][cc-by-image]][cc-by]\n\n[cc-by]: http://creativecommons.org/licenses/by/4.0/\n[cc-by-image]: https://i.creativecommons.org/l/by/4.0/88x31.png\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsantisoler%2Flapis2019","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsantisoler%2Flapis2019","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsantisoler%2Flapis2019/lists"}