************ The 1st Lab Seminar *************

Title: Denoising Methods for Thermomechanical Decomposition for Quasi-Equilibrium Molecular Dynamics Simulations
          A.C.To, Y.Fu, W.K.Liu, Comput. Methods Appl. Mech. Engrg. DOI:10.1016/j.cma.2011.03.004

Speaker: Takuya Okamoto

Date: Thu. May. 19th, 2:30 pm

Abstract:
In this work, we appliedrobust denoising methods well established in the signal processing
field for thethermomechanical decomposition of velocity data obtained from molecular dynamics
(MD) simulations. In the decomposition, the atomic velocity was assumed to be the sum of the
mechanical velocity and the thermal velocity, which can be linked to the stress and temperature
field at the continuum scale, respectively. For the quasi-equilibrium process, with the thermal
velocity treated as the Gaussian distributed stationary noise with zero mean and a positive
variance that is linearly proportional to temperature and mechanical velocity as the clean signal,
the velocity decomposition can be recasted into a denoising problem, for which powerful
denoising methods have been developed to estimate a clean signal from noisy data.We
investigatedthe widely-used linear parametric real-domain, linear nonparametric Fourier-based,
and nonlinear nonparametric wavelet-based denoising methods, first ontheir theoretical
properties and then made comparsion among them for denosing some synthetic noisy
1-dimensional (1D)data generated from MD simulations.The nonlinear wavelet-based
thresholding estimator possessed better optimality properties than the other estimators,and also
outperformed the other estimators in the synthetic data test. A further test comparing the various
denoising methodsfor an adiabatic shear crack nucleation and propagation process simulated
using MD simulationsshowedbetter performanceby the wavelet-based denoisng method.Results
from this work reveal good potential of applying wavelet-based denoising method to the study of
thermomechanical processes simulated using MD simulations.

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