Litcius/Paper detail

Data-driven methods for stress field predictions in random heterogeneous materials

Enjamamul Hoq, Osama Aljarrah, Jun Li, Jing Bi, Alfa Heryudono, Wenzhen Huang

2023Engineering Applications of Artificial Intelligence42 citationsDOI

Topics & Concepts

Computer scienceConvolutional neural networkConditional random fieldArtificial intelligenceRandom fieldMean squared errorMachine learningDeep learningAlgorithmStress fieldField (mathematics)Artificial neural networkFinite element methodMathematicsStatisticsThermodynamicsPure mathematicsPhysicsModel Reduction and Neural NetworksProbabilistic and Robust Engineering DesignNon-Destructive Testing Techniques
Data-driven methods for stress field predictions in random heterogeneous materials | Litcius