Error correction in multi-fidelity molecular dynamics simulations using functional uncertainty quantification
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[1] C. Chipot,et al. Cooperative Recruitment of Amphotericin B Mediated by a Cyclodextrin Dimer , 2014 .
[2] Peter A. Kollman,et al. FREE ENERGY CALCULATIONS : APPLICATIONS TO CHEMICAL AND BIOCHEMICAL PHENOMENA , 1993 .
[3] Simon Hanna,et al. Use of thermodynamic integration to calculate the hydration free energies of n-alkanes , 2002 .
[4] Christophe Chipot,et al. Good practices in free-energy calculations. , 2010, The journal of physical chemistry. B.
[5] Manuel Aldegunde,et al. Development of an exchange-correlation functional with uncertainty quantification capabilities for density functional theory , 2016, J. Comput. Phys..
[6] James Andrew McCammon,et al. Thermodynamic integration to predict host-guest binding affinities , 2012, Journal of Computer-Aided Molecular Design.
[7] Richard D. Hornung,et al. Adaptive sampling in hierarchical simulation , 2007 .
[8] A. Strachan,et al. Defect level distributions and atomic relaxations induced by charge trapping in amorphous silica , 2012 .
[9] Sophia Lefantzi,et al. DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. , 2011 .
[10] Steve Plimpton,et al. Fast parallel algorithms for short-range molecular dynamics , 1993 .
[11] Kipton Barros,et al. Distributed Database Kriging for Adaptive Sampling (D2KAS) , 2015, Comput. Phys. Commun..
[12] R. Jones,et al. Uncertainty quantification in MD simulations of concentration driven ionic flow through a silica nanopore. II. Uncertain potential parameters. , 2013, The Journal of chemical physics.
[13] A. O'Hagan,et al. Bayesian calibration of computer models , 2001 .
[14] A. Stukowski. Visualization and analysis of atomistic simulation data with OVITO–the Open Visualization Tool , 2009 .
[15] A. Hunter,et al. The role of partial mediated slip during quasi-static deformation of 3D nanocrystalline metals , 2015 .
[16] Enrique López Droguett,et al. Bayesian Methodology for Model Uncertainty Using Model Performance Data , 2008, Risk analysis : an official publication of the Society for Risk Analysis.
[17] George E. Karniadakis,et al. Quantification of sampling uncertainty for molecular dynamics simulation: Time-dependent diffusion coefficient in simple fluids , 2015, J. Comput. Phys..
[18] Sankaran Mahadevan,et al. Functional derivatives for uncertainty quantification and error estimation and reduction via optimal high-fidelity simulations , 2013 .
[19] Christophe Chipot,et al. Comprar Free Energy Calculations · Theory and Applications in Chemistry and Biology | Chipot, Christophe | 9783540736172 | Springer , 2007 .
[20] M. Karplus,et al. Molecular dynamics simulations in biology , 1990, Nature.
[21] Costas Papadimitriou,et al. Data driven, predictive molecular dynamics for nanoscale flow simulations under uncertainty. , 2013, The journal of physical chemistry. B.
[22] Simon R. Phillpot,et al. Uncertainty Quantification in Multiscale Simulation of Materials: A Prospective , 2013 .
[23] Andy J. Keane,et al. A Derivative Based Surrogate Model for Approximating and Optimizing the Output of an Expensive Computer Simulation , 2004, J. Glob. Optim..
[24] Ramana V. Grandhi,et al. A Bayesian statistical method for quantifying model form uncertainty and two model combination methods , 2014, Reliab. Eng. Syst. Saf..
[25] B. Roux,et al. Determination of membrane-insertion free energies by molecular dynamics simulations. , 2012, Biophysical journal.
[26] Jaroslaw Knap,et al. A call to arms for task parallelism in multi‐scale materials modeling , 2011 .
[27] P. A. Bash,et al. Free energy calculations by computer simulation. , 1987, Science.
[28] O. Knio,et al. Uncertainty quantification in MD simulations of concentration driven ionic flow through a silica nanopore. I. Sensitivity to physical parameters of the pore. , 2013, The Journal of chemical physics.
[29] Kipton Barros,et al. Spatial adaptive sampling in multiscale simulation , 2014, Comput. Phys. Commun..
[30] Berend Smit,et al. Understanding Molecular Simulation , 2001 .
[31] Jeremy E. Oakley,et al. When Is a Model Good Enough? Deriving the Expected Value of Model Improvement via Specifying Internal Model Discrepancies , 2014, SIAM/ASA J. Uncertain. Quantification.
[32] D. Frenkel. Free-energy calculations , 1991 .
[33] A. Strachan,et al. Multiscale contact mechanics model for RF–MEMS switches with quantified uncertainties , 2013 .
[34] J. Sethna,et al. Bayesian error estimation in density-functional theory. , 2005, Physical review letters.
[35] J. Tinsley Oden,et al. Selection, calibration, and validation of coarse-grained models of atomistic systems , 2015 .
[36] A. D. Kirshenbaum,et al. THE DENSITY OF LIQUID COPPER FROM ITS MELTING POINT (1356°K.) TO 2500°K. AND AN ESTIMATE OF ITS CRITICAL CONSTANTS1,2 , 1962 .
[37] Sankaran Mahadevan,et al. Model uncertainty and Bayesian updating in reliability-based inspection , 2000 .
[38] Paul N. Patrone,et al. Uncertainty quantification in molecular dynamics studies of the glass transition temperature , 2016 .
[39] Michael McLennan,et al. PUQ: A code for non-intrusive uncertainty propagation in computer simulations , 2015, Comput. Phys. Commun..
[40] Alejandro Strachan,et al. Uncertainty propagation in a multiscale model of nanocrystalline plasticity , 2011, Reliab. Eng. Syst. Saf..
[41] Ali Mosleh,et al. Integrated treatment of model and parameter uncertainties through a Bayesian approach , 2013 .
[42] F. RIZZI,et al. Uncertainty Quantification in MD Simulations. Part I: Forward Propagation , 2012, Multiscale Model. Simul..
[43] Ramana V. Grandhi,et al. A Bayesian approach for quantification of model uncertainty , 2010, Reliab. Eng. Syst. Saf..
[44] Costas Papadimitriou,et al. Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models , 2015, J. Comput. Phys..
[45] A. O'Hagan,et al. Predicting the output from a complex computer code when fast approximations are available , 2000 .
[46] Khachik Sargsyan,et al. Uncertainty Quantification in MD Simulations. Part II: Bayesian Inference of Force-Field Parameters , 2012, Multiscale Model. Simul..