The Preconditioned Conjugate Gradient (PCG) Block Lanczos eigensolver is a variant of the Block Lanczos method designed for large symmetric eigenvalue problems in modal analyses. It uses the same automated shift strategy but incorporates the PCG iterative solver instead of the sparse solver.
You can access this eigensolver by combining the Block Lanczos method (MODOPT,LANB) with the PCG solver (EQSLV,PCG). This combination triggers the new eigensolver automatically, which can improve performance and memory efficiency.
The default tolerance for the PCG Block Lanczos eigensolver is 1.0E-6.
Limitations
The PCG Block Lanczos eigensolver does not support the following:
Non-structural degrees of freedom (DOF)
Elements with U-P formulation/Lagrange multiplier method
Buckling analysis
Cyclic symmetry modal analysis
Automatic inertia relief (AIRL)
QRDAMP method
Modal analysis with superelements
Sturm sequence checks
GPU acceleration for modal analysis
Auto fall back to sparse solver