Comparative Study of Bending Analysis using Physics-Informed Neural Networks and Numerical Dynamic Deflection in Perforated nanobeam
📰 ArXiv cs.AI
Learn to analyze bending behavior in perforated nanobeams using Physics-Informed Neural Networks (PINNs) and numerical dynamic deflection methods
Action Steps
- Apply Physics-Informed Neural Networks (PINNs) to model the bending behavior of perforated nanobeams
- Use the Domain Mapping (DFL-TFC) method to improve computational efficiency
- Compare the static bending response and dynamic deflection of perforated nanobeams for various perforation cases
- Run numerical simulations to validate the results of the PINNs model
- Analyze the relationship between static bending response and dynamic deflection in perforated nanobeams
Who Needs to Know This
Researchers and engineers working on nanoscale structures and materials science can benefit from this study to improve their understanding of bending behavior in perforated nanobeams
Key Insight
💡 Physics-Informed Neural Networks (PINNs) can be used to efficiently model the bending behavior of perforated nanobeams
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🔍 Comparative study on bending analysis of perforated nanobeams using PINNs and numerical dynamic deflection methods 🚀
Key Takeaways
Learn to analyze bending behavior in perforated nanobeams using Physics-Informed Neural Networks (PINNs) and numerical dynamic deflection methods
Full Article
Title: Comparative Study of Bending Analysis using Physics-Informed Neural Networks and Numerical Dynamic Deflection in Perforated nanobeam
Abstract:
arXiv:2604.24768v1 Announce Type: cross Abstract: In this chapter, we investigate the bending behavior of a perforated nanobeam subjected to sinusoidal loading using an efficient and computationally robust Physics-Informed Functional Link Constrained Framework with Domain Mapping (DFL-TFC) method. Our aim is to determine the relationship between static bending response and dynamic deflection of a perforated nanobeam for various perforation cases. The static bending is obtained using the FL-TFC w
Abstract:
arXiv:2604.24768v1 Announce Type: cross Abstract: In this chapter, we investigate the bending behavior of a perforated nanobeam subjected to sinusoidal loading using an efficient and computationally robust Physics-Informed Functional Link Constrained Framework with Domain Mapping (DFL-TFC) method. Our aim is to determine the relationship between static bending response and dynamic deflection of a perforated nanobeam for various perforation cases. The static bending is obtained using the FL-TFC w
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