...which can adversely affect solver performance. Consider using the Pinball setting to reduce the number of elements included in the solver.

Remote boundary conditions scoped to a large number of elements can cause the solver to consume excessive amounts of memory. Point masses in an analysis where a mass matrix is required and analyses that contain remote displacements are the most sensitive to this phenomenon. If this situation occurs, consider modifying the Pinball setting to reduce the number of elements included in the solver. Forcing the use of an iterative solver may help as well.

The reason for the excessive memory consumption is that the remote boundary conditions generate internal constraint equations to distribute the remote mass, displacement, or loads from one node of the model to all other selected nodes. As described in Chapter 15.14. Constraint Equations, in the Mechanical APDL Theory Reference, constraint equations could change a sparse matrix (for example, a stiffness matrix, mass matrix, or damping matrix) to a dense matrix. An increase in the number of constraint equations used increases the density of the final matrix, which in turn places a higher demand for more memory (or longer CPU time) in the solution of a problem.

Normally, if the maximum number of remote nodes selected is about 3000, then the increased memory usage or CPU time is not significant. Caution should be taken to not use too many remote nodes in these applications. Other techniques are available to distribute loads or masses. For example, to distribute a point mass to the entire model, you might consider specifying density directly instead of using the point mass approach.