Conformal mapping based Physics-informed neural networks for designing neutral inclusions

Key Points

• The approach shows significant improvements in inclusion design efficiency and accuracy.
• Key evidence includes enhanced modeling performance, demonstrating up to 40% reduction in error rates.
• Analysis employs conformal mapping along with physics-informed neural networks to optimize designs effectively.
• This may enable advancements in materials science, supporting innovative structural designs and applications.