Simulations Used in Geotechnical Practice: Part 1 - Comparing Monte Carlo and Latin Hypercube Sampling

Monte Carlo (MC) sampling is the traditional technique for generating random numbers to sample from a probability distribution. When low probability events occur, a small number of MC iterations might not sample sufficient quantities of these outcomes for inclusion in the simulation model. Latin Hypercube (LH) sampling uses stratification of the input probability distributions, to overcome the limitations of Monte Carlo sampling. Both the LH and MC sampling are compared to demonstrate this effect in common geotechnical engineering simulation applications. These simulation results show the LH better represents low probability outcomes by forcing the sampling of the simulation to include outlying events. At a high number of simulation iterations both provide similar outputs, but at low simulation iterations the LH is more reliable. A companion paper (Part 2) factors in the probability density function (PDF) used. Non-normal PDFs often represent the best fit PDF when a goodness of fit test is carried out

Keywords: Simulation, Monte Carlo, Latin Hypercube, Probability density functions