Accelerating Monte Carlo Molecular Simulations Using Novel Extrapolation Schemes Combined with Fast Database Generation on Massively Parallel Machines

In this paper we introduce efficient thermodynamically consistent techniques to extrapolate and interpolate normalized Canonical NVT ensemble averages for Lennard-Jones (L-J) fluids at different thermodynamic conditions from expensively simulated data points. This leads to a significant speed up in generating intensive data. Preliminary results show promising applicability in oil and gas modelling. To investigate the efficiency of these methods, two databases corresponding to different combinations of normalized density and temperature values are generated. One contains 175 Markov chains each with 10,000,000 MC cycle results and the other contains 3000 Markov chains with 61,000,000 MC cycle results. The relative error of the thermodynamic extrapolation and thermodynamic interpolation schemes were investigated with respect to classical interpolation and extrapolation. Index Terms – Molecular Simulation, Monte Carlo, Canonical Ensemble, Lennard-Jones Fluid, Extrapolation, and Interpolation.