Toru Yamada

This study proposes an application of Nosé–Hoover (NH) dynamics as a coarse-graining (CG) method for molecular simulations, offering an alternative to traditional Langevin-based approaches. The NH dynamics, known for its deterministic temperature control without stochastic forces, is adapted here to model a monoatomic Lennard-Jones system at different coarse-grained levels. The CG particle’s equation of motion is derived from atomic-level dynamics, linking NH thermostat terms with system properties obtained from molecular dynamics (MD) simulations. Key parameters, including the thermostat coefficient and thermal inertia, are calibrated using the MD data to assess their impact on the dynamic and structural reproducibility of the CG model. The calibration results suggest the potential application of NH dynamics as a coarse-graining method. The effectiveness of the proposed method is then evaluated through a set of CG simulations. The CG results show stable energy regulation and promising accuracy in reproducing system properties, particularly for mass diffusion, with opportunities for further refinement in representing structural reproducibility and momentum diffusion.

The drag-reducing effects of two nonionic-type surfactants, oleyl-N, N-dimethylamine N-oxide (ODMAO) and octadecyl-N, N-bis(2-hydroxyethyl)amine N-oxide (C18BAO), in ethylene glycol (EG) aqueous solution were comprehensively investigated at various surfactant concentrations of up to 2000 ppm by weight at various solution temperatures ranging from −5 to 80 °C in turbulent pipe flows. In EG aqueous solution (30% by weight), the mixture of ODMAO with salicylic acid with a molar ratio of 0.2 could effectively reduce the turbulent drag in the low-temperature range (up to 40 °C), whereas the effect of C18BAO was more notable at a temperature higher than 40 °C. Furthermore, the mixture of ODMAO and C18BAO in EG aqueous solution exhibited a high drag reduction ratio of more than 60% in a considerably wider range of solution temperatures (from 20 to 60 °C), while the drag reduction performance deteriorated below 0 °C and beyond 60 °C.

This study puts emphasis on reducing the temperature error of dissipative particle dynamics (DPD) fluid by directly applying a minimal-stage third-order partitioned Runge-Kutta (PRK3) method to the time integration, which does not include any of additional governing equations and change in the DPD thermostat formulation. The error is estimated based on the average values of both kinetic and configurational temperatures. The result shows that the errors in both temperatures errors are greatly reduced by using the PRK3 scheme as comparing them to those of previous studies. Additionally, the comparison among three different PRK3 schemes demonstrates our recent findings that the symplecticity conservation of the system is important to reduce the temperature error of DPD fluid especially for large time increments. The computational efficiencies are also estimated for the PRK3 scheme as well as the existing ones. It was found from the estimation that the simulation using the PRK3 scheme is more than twice as efficient as those using the existing ones. Finally, the roles of both kinetic and configurational temperatures as error indicators are discussed by comparing them to the velocity autocorrelation function and the radial distribution function. It was found that the errors of these temperatures involve different characteristics, and thus both temperatures should be taken into account to comprehensively evaluate the numerical error of DPD.

This study was focused on improving the numerical accuracy of the dissipative particle dynamics simulation via modifying its numerical time integration scheme. Despite the integration of the pairwise Langevin part dealt with by most of the previous studies, we paid attention to the improvement of the standard Liouville part. The numerical accuracy was measured by the configurational temperature in this study. Employing a fourth order symplectic scheme showed a significant improvement of the numerical accuracy for the simulations especially with a large time increment when comparing it with existing schemes, which indicates that enough resolution in time was attained when our modified scheme was employed. In addition, a set of simulations was performed for a wider range of time increments than previous studies. The results showed that the computational error demonstrated different orders of accuracy for different time increment ranges, which led to the fact that the dominant effect on the error is conservative and random forces for the large and small increment ranges.

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The effects of temperature-dependent thermophysical properties on droplet flow characteristics in a parallel-plate channel at submicron scale are investigated. The dissipative particle dynamics method with many-body (MDPD) and energy conservation (DPDe) configurations (MDPDe) was used. Droplet flows were simulated to study the effects of the temperature difference between top and bottom walls, body force on MDPDe particles, and wall-wetting conditions. The effects on the droplet flow were discussed. Droplet flows with a subzero wall temperature were simulated. An ice layer was formed on the wall. Its thickness and shape changed depending on surface wetting, temperature gradient, and body force.