Hybrid Shell-Beam Inverse Finite Element Method for the Shape Sensing of Stiffened Thin-Walled Structures:...

Area of Science:

• Structural Mechanics
• Computational Engineering
• Materials Science

Background:

• Accurate elastic deformation reconstruction is crucial for structural health monitoring.
• Traditional inverse finite element methods (iFEM) face limitations with complex geometries.
• Element selection significantly impacts iFEM accuracy and computational cost.

Purpose of the Study:

• To develop a novel hybrid discretization scheme for iFEM.
• To improve the accuracy and efficiency of shape-sensing for thin-walled and stiffened structures.
• To enable more effective digital twin development for online structural monitoring.

Main Methods:

• A hybrid iFEM model combining beam and shell inverse elements was developed.
• The methodology reconstructs structural displacements from discrete strain measurements.
• Least-squares matching of analytical and experimental strains was employed.

Main Results:

• Experimental validation on a composite wing panel demonstrated accurate shape sensing of bending and torsional deformations.
• The hybrid iFEM achieved high accuracy with reduced sensor measurements and computational effort.
• The method proved robust and computationally efficient.

Conclusions:

• The hybrid iFEM offers a significant advancement for accurate and efficient structural shape sensing.
• This approach facilitates the development of digital twins for real-time structural monitoring and control.
• The methodology is well-suited for geometrically complex, thin-walled, and stiffened structures.