{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/171205737","title":"Acceleration Profiles and Processing Methods for Parabolic Flight","arxiv_id":"1712.05737","date":"2017-12-15","proceeding":null,"authors":["Christopher E. Carr","Noelle C. Bryan","Kendall N. Saboda","Srinivasa A. Bhattaru","Gary Ruvkun","Maria T. Zuber"],"abstract":"Parabolic flights provide cost-effective, time-limited access to \"weightless\" or reduced gravity conditions experienced in space or on planetary surfaces, e.g. the Moon or Mars. These flights facilitate fundamental research - from materials science to space biology - and testing/validation activities that support and complement infrequent and costly access to space. While parabolic flights have been conducted for decades, reference acceleration profiles and processing methods are not widely available - yet are critical for assessing the results of these activities. Here we present a method for collecting, analyzing, and classifying the altered gravity environments experienced during a parabolic flight. We validated this method using a commercially available accelerometer during a Boeing 727-200F flight with $20$ parabolas. All data and analysis code are freely available. Our solution can be easily integrated with a variety of experimental designs, does not depend upon accelerometer orientation, and allows for unsupervised and repeatable classification of all phases of flight, providing a consistent and open-source approach to quantifying gravito-intertial accelerations (GIA), or $g$ levels. As academic, governmental, and commercial use of space increases, data availability and validated processing methods will enable better planning, execution, and analysis of parabolic flight experiments, and thus, facilitate future space activities.","url_abs":"http://arxiv.org/abs/1712.05737v1","url_pdf":"http://arxiv.org/pdf/1712.05737v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"171205737","repo_url":"https://github.com/CarrCE/zerog","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"171205737","repo_url":"https://github.com/CarrCE/zerogseq","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}