
This dataset contains 2D dynamic non-linear structural mechanics with a non-linear non-local constitutive law. The files format is PLAID, see the plaid documentation. The variablity in the samples is the geometry (mesh). Outputs of interest are 3 transient fields: x and y components of the displacement at the nodes and the erosion status at the elements. The dataset has a training set of size 1000 and a testing set of size 18. Outputs are not provided on the testing sets. Tips to access the data: After decompressing the downloaded file: from plaid.containers.dataset import Datasetfrom plaid.problem_definition import ProblemDefinition dataset = Dataset()problem = ProblemDefinition() problem._load_from_dir_(os.path.join(/path/to/data,'problem_definition'))dataset._load_from_dir_(os.path.join(/path/to/data,'dataset'), verbose = True) print("problem =", problem)print("dataset =", dataset) ids_train = problem.get_split('train') ids_test = problem.get_split('test') sample_train_0 = dataset[ids_train[0]] sample_test_0 = dataset[ids_test[0]] print(sample_train_0) print(sample_test_0) sample = sample_train_0 # inputs mesh = sample.get_mesh() mesh = sample.get_mesh(time=0.01, apply_links=True, in_memory=True)# links to mesh at time=0 since mesh is constant print(mesh) # outputs for fn in ["U_x", "U_y"]: field = sample.get_field(fn, time=0.01) print(field) field = sample.get_field("EROSION_STATUS", location="CellCenter", time=0.01) print(field)
AI, Physics, Machine learning, Geometrical variations, Simulation, Structural mechanics
AI, Physics, Machine learning, Geometrical variations, Simulation, Structural mechanics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
