{"url":"/dataset/nasa-c-mapss","name":"NASA C-MAPSS","full_name":"Turbofan Engine Degradation Simulation Data Set","description_markdown":"Engine degradation simulation was carried out using C-MAPSS. Four different were sets simulated under different combinations of operational conditions and fault modes. Records several sensor channels to characterize fault evolution. The data set was provided by the Prognostics CoE at NASA Ames.","description_withheld":null,"homepage":"https://ti.arc.nasa.gov/tech/dash/groups/pcoe/prognostic-data-repository/","introduced_date":"2008-01-01","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Time series","url":"/datasets/modality/time-series"}],"tasks":[{"name":"Decision Making","url":"/task/decision-making","datasets_with_task":"/datasets/task/decision-making"},{"name":"Remaining Useful Lifetime Estimation","url":"/task/remaining-useful-lifetime-estimation","datasets_with_task":"/datasets/task/remaining-useful-lifetime-estimation"},{"name":"reinforcement-learning","url":"/task/reinforcement-learning-2","datasets_with_task":"/datasets/task/reinforcement-learning-2"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["NASA C-MAPSS"],"data_loaders":[],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/decision-making-on-nasa-c-mapss","task":"Decision Making","dataset_variant":"NASA C-MAPSS","rows":1,"metrics":["Average Remaining Cycles"],"first_row_in_archive_order":{"model":"SRLA","paper":"/paper/hierarchical-framework-for-interpretable-and","metrics":{"Average Remaining Cycles":"6.4"},"code_links":[{"title":"ammar-n-abbas/Predictive-Maintenance-BC-IOHMM-DRL","url":"https://github.com/ammar-n-abbas/Predictive-Maintenance-BC-IOHMM-DRL"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/remaining-useful-lifetime-estimation-on-nasa-1","task":"Remaining Useful Lifetime Estimation","dataset_variant":"NASA C-MAPSS","rows":1,"metrics":["RMSE"],"first_row_in_archive_order":{"model":"RVE","paper":"/paper/variational-encoding-approach-for","metrics":{"RMSE":"14.92"},"code_links":[{"title":"NahuelCostaCortez/Remaining-Useful-Life-Estimation-Variational","url":"https://github.com/NahuelCostaCortez/Remaining-Useful-Life-Estimation-Variational"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/hierarchical-framework-for-interpretable-and","title":"Hierarchical Framework for Interpretable and Probabilistic Model-Based Safe Reinforcement Learning","date":"2023-10-28","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/variational-encoding-approach-for","title":"Variational encoding approach for interpretable assessment of remaining useful life estimation","date":"2022-02-23","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}