Deformation Analysis in Elastic Solids

Related lectures (25)

Page 2 of 3

Covers matrix operations, focusing on the product and inverse of matrices.

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.

Explains the inertia tensor, main axes, principal moments, and balancing of rotating solids.

Explores the definition and properties of the metric tensor, enabling control of geometric quantities and lengths.

Covers the concept of the matrix of cofactors and a formula to calculate the inverse of a matrix.

Explores deformation and strain tensors, Lagrange representation, elasticity theory, and the divergence theorem.

Explores matrix inversion, conditions for invertibility, uniqueness of the inverse, and elementary matrices for inversion.

Explores the Jacobi method and diagonalization techniques, including similarity transformation, power methods, and QR decomposition.

Covers direct methods for solving linear systems in numerical analysis.

Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.