A neural network-based approach for bending analysis of strain gradient nanoplates

• Published in: Engineering analysis with boundary elements Vol. 146; pp. 517 - 530
• Main Authors: Yan, C.A., Vescovini, R., Fantuzzi, N.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2023
• Subjects: Bending analysis; Extreme Learning Machine; Nanoplates; Parameter identification; Physics-Informed Neural Networks; Strain gradient theory; Bending analysis; Physics-Informed Neural Networks; Extreme Learning Machine; Nanoplates; Strain gradient theory; Parameter identification

Purpose of this paper is the presentation of a novel Machine Learning (ML) technique for nanoscopic study of thin nanoplates. The second-order strain gradient theory is used to derive the governing equations and account for size effects. The ML framework is based on Physics-Informed Neural Networks...