END-TO-END PREDICTION OF MULTIMATERIAL STRESS FIELDS AND FRACTURE PATTERNS USING CYCLE-CONSISTENT ADVERSARIAL AND TRANSFORMER NEURAL NETWORKS

The prediction of stress, strain fields or fracture patterns, along with other physical quantities as a function of boundary conditions and material microstructure, is an important objective of various physics-based simulation methods like finite element models or molecular dynamics modeling.However, such simulations may be expensive and can be cos

ABSTRACT The digital data stored in the cloud requires much space due to copy of the same data.It can be reduced by dedupilcation, eliminating the copy of the repeated data in the cloud provided services.Identifying common checkoff data both files storing them only once.Deduplication can yield cost savings by increasing the utility of a given amoun