Numerical analysis is a valuable tool to support the decision-making process in geotechnical design. Such analyses might still remain excessively time-consuming if FE models are not being set up properly, if possible convergence issues cannot be quickly identified and, should they arise, if they cannot be efficiently troubleshot. This article provides a set of recommendations on the various ways you can speed up calculation time and make an even better return on your FEA investment.
Calculation time in PLAXIS is directly related to the mesh size. The more elements a mesh contains, the larger the stiffness matrix of the system (that needs to be inverted) and the longer the calculation time will be. It is therefore very important to define the optimal model dimension and even more crucial to introduce an appropriate level of mesh refinement, and only where it really matters.
The first recommendation one could provide is to model and mesh only what is necessary. For instance, always start by identifying symmetry conditions and make use of them (this could be plane symmetry for excavation, cyclic symmetry for quay wall, etc.). In this manner, you could significantly reduce the number of elements and, consequently, associated calculation time.
Mesh needs to be refined only in areas where large stress gradients are expected to develop. Typically, finer mesh density is required close to structures and can grow coarser moving toward the model boundaries where element size could be significantly larger. Mesh refinement zones can be advantageously defined by sets of surfaces enclosing the soil area, the mesh of which could be refined. This way, you can limit the volume over which mesh is refined.
The calculation progress window as shown in Figure 2 provides a handful of interesting information pieces to be considered when evaluating the convergence rate of a given calculation. It will help users identify any convergence issues that could result in excessively long calculation time before the calculation kernel could even determine that reaching full convergence cannot possibly be reached. The key items in the calculation progress window are:
The PLAXIS calculation kernel provides access to a log file to help you understand the convergence behavior of your analysis and debug the model if necessary. The file includes a summary of all convergence criteria for each step, attempt, and iteration of a given phase analysis. This diagnostic information is saved automatically for every analysis being run. If an analysis takes longer than expected or terminates prematurely, you can view the logging information in any editor to help determine the cause(s) and to identify ways to correct the model accordingly.
Many PLAXIS calculation projects are composed of multiple independent phases, often introduced for the analysis of multiple scenarios from a common construction history (as shown in Figure 3b). By default, any PLAXIS calculation phase will dedicate all available calculation cores of the machine for each phase, irrespective of their level of interdependency.
However, by assuming just one single core to each calculation phase, independent phases can be run simultaneously on the same calculation machine. This saves you a considerable amount of time compared to having to run them all in a series.
PLAXIS 3D offer two types of solvers:
For the majority of geotechnical problems, the PICOS iterative solver is the most efficient, which explains why this is the solver that PLAXIS 3D calculation opts for by default.
The main advantage of the iterative solver is its memory usage, which is significantly less than a direct solver for the same sized problems. For well-conditioned problems, it converges also considerably faster compared to a direct solver, with a time gain increasing as the number of elements grows larger.
However, for geotechnical problems and for not well-conditioned problems (for instance, an extremely large difference of stiffnesses in stress analyses or permeabilities values in flow or consolidation problems), the PARDISO direct solver usually performs better and therefore faster compared to PICOS. The PARDISO solver will require a substantially larger amount of memory (considerably more than the PICOS solver would), but will provide faster solutions for such not well-conditioned problems.
Watch LinkedIn Live Session, by Richard Witasse, sharing tips for speeding up mesh generation, as well as calculation time.
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