{"url":"/dataset/pino-plate-stress","name":"PINO-plate-stress","full_name":null,"description_markdown":"This dataset is well-structured for the physics-informed training of Neural operators for irregular domain geometry, which provides the FEM results of solving a 2D plate stress problem in a domain geometry shape of a rectangle with a hole. The Github of the paper that first use this dataset is: https://github.com/WeihengZ/PI-DCON.","description_withheld":null,"homepage":"https://drive.google.com/drive/folders/10c5BWVvd-Oj13tMGhE07Tau07aTWfOhM","introduced_date":"2024-04-21","introduced_date_note":null,"introduced_by":{"paper":"/paper/physics-informed-mesh-independent-deep","title":"Physics-informed Discretization-independent Deep Compositional Operator Network","first_author":"Weiheng Zhong","url":null},"license":null,"modalities":[],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["PINO-plate-stress"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}