The Multiscale Hybrid Method with a Localized Constraint. II. Hybrid Equations of Motion Based on Variational Principles

Authors

  • M. Bakumenko Taras Shevchenko National University of Kyiv, Aston University
  • V. Bardik Taras Shevchenko National University of Kyiv
  • V. Farafonov V.N. Karazin Kharkiv National University
  • D. Nerukh Aston University

DOI:

https://doi.org/10.15407/ujpe69.4.269

Keywords:

molecular dynamics, multiscale method, control volume function, hydrodynamic equations, equation of motion, Principle of least action, Gauss principle, constraint

Abstract

A multiscale modelling framework that employs molecular dynamics and hydrodynamics principles has been developed to describe the dynamics of hybrid particles. Based on the principle of least action, the equations of motion for hybrid particles were derived and verified by using the Gauss principle of least constraints testifying to their accuracy and applicability under various system constraints. The proposed scheme has been implemented in a popular open-source molecular dynamics code GROMACS. The simulation for liquid argon under equilibrium conditions in the hydrodynamic limit (s = 1) has demonstrated that the standard deviation of the density exhibits a remarkable agreement with predictions from a pure hydrodynamics model, validating the robustness of the proposed framework.

References

G. Ayton, G.A. Voth. Bridging microscopic and mesoscopic simulations of lipid bilayers. Biophys. J. 83, 3357 (2002).

https://doi.org/10.1016/S0006-3495(02)75336-8

M. Bakumenko, V. Bardik, D. Nerukh. The multiscale hybrid method with a localized constraint. I. A modified control volume function for the hybridized mass and momentum equations. Ukr. J. Phys. 68, 8 (2023).

https://doi.org/10.15407/ujpe68.8.517

A.M. Bloch. Nonholonomic Mechanics and Control (Springer, 2003).

https://doi.org/10.1007/b97376

E. Smith. On the Coupling of Molecular Dynamics to Continuum Computational Fluid Dynamics (Imperial College London, 2013).

G. De Fabritiis, R. Delgado-Buscalioni, P.V. Coveney. Multiscale modeling of liquids with molecular specificity. Phys. Rev. Lett. 97 (13), 134501 (2006).

https://doi.org/10.1103/PhysRevLett.97.134501

M.R. Flannery. The elusive d'Alembert-Lagrange dynamics of nonholo-nomic systems. American J. Phys. 79, 932 (2011).

https://doi.org/10.1119/1.3563538

M.R. Flannery. D'Alembert-Lagrange analytical dynamics for nonholo-nomic systems. J. Math. Phys. 52 (3), 032705 (2011).

https://doi.org/10.1063/1.3559128

M.R. Flannery. The enigma of nonholonomic constraints. Am. J. Phys. 73 (3), 265 (2005).

https://doi.org/10.1119/1.1830501

E.G. Flekkoy, G. Wagner, J. Feder. Hybrid model for combined particle and continuum dynamics. Europhysics Lett. 52, 271 (2000).

https://doi.org/10.1209/epl/i2000-00434-8

D. Freedman, R. Pisani, R. Purves. Statistics (W.W. Norton & Company, 2007).

H. Goldstein, C. Poole, J. Safko. Classical mechanics. American J. Phys. 70 (7), 782 (2002).

https://doi.org/10.1119/1.1484149

D.T. Greenwood. Advanced Dynamics (Cambridge University Press, 2003).

https://doi.org/10.1017/CBO9780511800207

J. Hu, I.A. Korotkin, S.A. Karabasov. A multi-resolution particle/fluctuating hydrodynamics model for hybrid simulations of liquids based on the two-phase flow analogy. J. Chem. Phys. 149 (8), 084108 (2018).

https://doi.org/10.1063/1.5040962

J.H. Irving, J.G. Kirkwood. The statistical mechanical theory of transport processes. IV. The equations of hydrodynamics. J. Chem. Phys. 18 (6), 817 (1950).

https://doi.org/10.1063/1.1747782

P.M. Kasson, V.S. Pande. Cross-graining: Efficient multiscale simu-lation via Markov state models. Pacific Symposium on Biocomputing 15, 260 (2010).

https://doi.org/10.1142/9789814295291_0028

I. Korotkin, S. Karabasov, D. Nerukh et al. A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time. J. Chem. Phys. 143 (1), 014110 (2015).

https://doi.org/10.1063/1.4923011

I.A. Korotkin, S.A. Karabasov. A generalised Landau-Lifshitz fluctuating hydrodynamics model for concurrent simulations of liquids at atomistic and continuum resolution. J. Chem. Phys. 149 (24), 244101 (2018).

https://doi.org/10.1063/1.5058804

E. Kotsalis, J. Walther, E. Kaxiras, P. Koumoutsakos. Control algorithm for multiscale flow simulations of water. Phys. Revi. E 79 (4), 045701(R) (2009).

https://doi.org/10.1103/PhysRevE.79.045701

R. Lonsdale et al. A multiscale approach to modelling drug metabolism by membrane-bound cytochrome P450 enzymes. PLoS Computational Biology 10, e1003714 (2014).

https://doi.org/10.1371/journal.pcbi.1003714

A. Markesteijn, S. Karabasov, A. Scukins et al. Concurrent multiscale modelling of atomistic and hydrodynamic processes in liquids. Philos. Trans. R. Soc. A 372 (2021), 20130379 (2014).

https://doi.org/10.1098/rsta.2013.0379

J. Marrink et al. The MARTINI force field: Coarse grained model for biomolecular simulations. J. Phys. Chem. B 111 (27), 7812 (2007).

https://doi.org/10.1021/jp071097f

G.P. Morriss, C.P. Dettman. Thermostats: Analysis and application. Chaos 8 (2), 321 (1998).

https://doi.org/10.1063/1.166314

N. Nangia, H. Johansen, N. Patanka et al. A moving control volume approach to computing hydro- dynamic forces and torques on immersed bodies. J. Computational Phys. 347, 437 (2017).

https://doi.org/10.1016/j.jcp.2017.06.047

X.B. Nie, S.Y. Chen, W.N. E, M.O. Robbins. A continuum and molecular dynamics hybrid method for micro-and nano-fluid flow. J. Fluid Mech. 500, 55 (2004).

https://doi.org/10.1017/S0022112003007225

S.T. O'Connell, P.A. Thompson. Molecular dynamics-continuum hybrid computations: A tool for studying complex fluid flows. Phys. Rev. E 52 (6), R5792 (1995).

https://doi.org/10.1103/PhysRevE.52.R5792

J.T. Padding, W.J. Briels. Systematic coarse-graining of the dynamics of entangled polymer melts: The road from chemistry to rheology. J. Phys.: Condensed Matter 23, 233101 (2011).

https://doi.org/10.1088/0953-8984/23/23/233101

J.T. Padding, W.J. Briels. Time and length scales of polymer melts studied by coarse-grained molecular dynamics simulations. J. Chem. Phys. 117, 925 (2002).

https://doi.org/10.1063/1.1481859

E. Pavlov, M. Taiji, A. Scukins et al. Visualising and controlling the flow in biomolecular systems at and between multiple scales: from atoms to hydrodynamics at different locations in time and space. Faraday Discussions 169, 285 (2014).

https://doi.org/10.1039/C3FD00159H

C.S. Peskin. The immersed boundary method. Acta Numerica 11, 479 (2002).

https://doi.org/10.1017/S0962492902000077

E.J. Saletan, A.H. Cromer. A variational principle for nonholonomic systems. American J. Phys. 38 (7), 892 (1970).

https://doi.org/10.1119/1.1976488

E.R. Smith, D.M. Heyes, D. Dini, T.A. Zak. A localized momentum constraint for non-equilibrium molecular dynamics simulations. J. Chem. Phys. 142 (7), 074110 (2015).

https://doi.org/10.1063/1.4907880

N.A. Spenley. Scaling laws for polymers in dissipative particle dynamics. Europhys. Lett. 49, 534 (2000).

https://doi.org/10.1209/epl/i2000-00183-2

V. Symeonidis, G. Em Karniadakis, B. Caswell. Dissipative particle dynamics simulations of polymer chains: Scaling laws and shearing response compared to DNA experiments. Phys. Rev. Lett. 95, 076001 (2005).

https://doi.org/10.1103/PhysRevLett.95.076001

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Published

2024-05-30

How to Cite

Bakumenko, M., Bardik, V., Farafonov, V., & Nerukh, D. (2024). The Multiscale Hybrid Method with a Localized Constraint. II. Hybrid Equations of Motion Based on Variational Principles. Ukrainian Journal of Physics, 69(4), 269. https://doi.org/10.15407/ujpe69.4.269

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Section

Physics of liquids and liquid systems, biophysics and medical physics