{"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/fake-it-till-you-make-it-using-artificial","title":"Fake it till you make it: using artificial turbulence to achieve swift converged turbulence statistics in a pressure-driven channel flow","arxiv_id":"2411.11416","date":"2024-11-18","proceeding":null,"authors":["Akshay Patil","Clara García-Sánchez"],"abstract":"In this study, we introduced a simple yet innovative method to trigger turbulence in a channel flow to achieve statistically stationary flow conditions. We compare this new method based on synthetically generated three-dimensional turbulence with two other well-established methods, namely, linear profile superposed with random noise and descending counter-rotating vortices and log-law profile superposed with random noise and descending counter-rotating vortices. We found that synthetically generated three-dimensional turbulence provides a computationally cheap and effective way to reduce simulation spin-up to achieve statistically stationary flow conditions when a precursor turbulent initial condition is not available. At a one-time cost of less than 1 CPU hour to generate the synthetic turbulent initial condition, the flow becomes statistically stationary within 3 eddy turnovers for all the parameters of interest in wall-bounded pressure-driven channel flow simulations when compared to other alternatives that can take more than 10 eddy turnovers resulting in substantial savings in the computational cost.","url_abs":"https://arxiv.org/abs/2411.11416v1","url_pdf":"https://arxiv.org/pdf/2411.11416v1.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":"fake-it-till-you-make-it-using-artificial","repo_url":"https://github.com/AkshayPatil1994/transition_data","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"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}