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We propose a novel structure preserving discretization for viscous and resistive magnetohydrodynamics. We follow the recent line of work on discrete least action principle for fluid and plasma equation, incorporating the recent advances to…

Numerical Analysis · Mathematics 2025-04-09 Valentin Carlier

The new mathematical framework based on the free energy of pure classical fluids presented in [R. D. Rohrmann, Physica A 347, 221 (2005)] is extended to multi-component systems to determine thermodynamic and structural properties of…

Statistical Mechanics · Physics 2008-11-26 R. D. Rohrmann , J. Zorec

A parameterization strategy for molecular models on the basis of force fields is proposed, which allows a rapid development of models for small molecules by using results from quantum mechanical (QM) ab initio calculations and thermodynamic…

Chemical Physics · Physics 2009-04-22 Bernhard Eckl , Jadran Vrabec , Hans Hasse

In this paper we propose a dual-time stepping scheme for the Smoothed Particle Hydrodynamics (SPH) method. Dual-time stepping has been used in the context of other numerical methods for the simulation of incompressible fluid flows. Here we…

Computational Physics · Physics 2021-06-25 Prabhu Ramachandran , Abhinav Muta , Ramakrishna Mokkapati

Aims. In this work we rigorously show the shortcomings of various simplifications that are used to calculate the total internal partition function. These shortcomings can lead to errors of up to 40 percent or more in the estimated partition…

Chemical Physics · Physics 2016-11-16 Andrius Popovas , Uffe G. Jørgensen

In this paper, we extend the adaptive partition-based approach for solving two-stage stochastic programs with fixed recourse to the multistage stochastic programming setting. The proposed algorithms integrate the adaptive partition-based…

Optimization and Control · Mathematics 2019-08-30 Murwan Siddig , Yongjia Song

In this work we developed a method for simulating polar species in the dissipative particle dynamics (DPD) method. The main idea behind the method is to treat each bead as a dumb-bell, i.e. two sub-beads (the sub-beads can bear charges)…

Computational Physics · Physics 2020-04-24 Alexey A. Gavrilov

Dynamic Mode Decomposition (DMD) is a data-driven and model-free decomposition technique. It is suitable for revealing spatio-temporal features of both numerically and experimentally acquired data. Conceptually, DMD performs a…

Fluid Dynamics · Physics 2020-12-18 Tim Krake , Stefan Reinhardt , Marcel Hlawatsch , Bernhard Eberhardt , Daniel Weiskopf

Isothermal-isobaric molecular dynamics simulations are used to examine the microscopic structure and some properties of water-methanol liquid mixture. The TIP4P/2005 and SPC/E water models are combined with the united atom TraPPE and the…

Soft Condensed Matter · Physics 2019-03-28 M. Cruz Sanchez , H. Dominguez , O. Pizio

We developed a portable code for dissipative particle dynamics (DPD) simulations. This Fortran program named CAMUS has a couple of notable features. One is the omission of constructing the so-called neighboring particles list, providing a…

Chemical Physics · Physics 2018-07-03 Hideo Doi , Koji Okuwaki , Takamitsu Naito , Sona Saitou , Yuji Mochizuki

Dynamic mode decomposition (DMD) is a recently developed tool for the analysis of the behavior of complex dynamical systems. In this paper, we will propose an extension of DMD that exploits low-rank tensor decompositions of potentially…

Numerical Analysis · Mathematics 2019-08-14 Stefan Klus , Patrick Gelß , Sebastian Peitz , Christof Schütte

The physical foundations of the dissipation of energy and the associated heating in weakly collisional plasmas are poorly understood. Here, we compare and contrast several measures that have been used to characterize energy dissipation and…

Data assimilation algorithms estimate the state of a dynamical system from partial observations, where the successful performance of these algorithms hinges on costly parameter tuning and on employing an accurate model for the dynamics.…

Machine Learning · Statistics 2026-03-24 Melissa Adrian , Daniel Sanz-Alonso , Rebecca Willett

Density-potential functional theory (DPFT) is an alternative formulation of orbital-free density functional theory that may be suitable for modeling the electronic structure of large systems. To date, DPFT has been applied mainly to quantum…

Materials Science · Physics 2023-04-21 Martin-Isbjörn Trappe , William C. Witt , Sergei Manzhos

This article reports about a novel extension of dissipative particle dynamics (DPD) that allows the study of the collective dynamics of complex chemical and structural systems in a spatially resolved manner with a combinatorially complex…

Subcellular Processes · Quantitative Biology 2011-12-07 Rudolf M. Fuechslin , Thomas Maeke , John S. McCaskill

We have developed an efficient and unconditionally energy-stable method for simulating droplet formation dynamics. Our approach involves a novel time-marching scheme based on the scalar auxiliary variable technique, specifically designed…

Numerical Analysis · Mathematics 2024-02-08 Jinpeng Zhang , Changjuan Zhang , Xiaoping Wang

In this work we consider the semi-batch process of precipitation of calcium carbonate solids from a solution containing calcium ions by adjusting the pH of the solution. The change in pH is induced either by the addition of alkaline…

Optimization and Control · Mathematics 2025-08-14 Sandesh Athni Hiremath , Chinmay Hegde , Andreas Voigt

Particle flow (PFL) is an effective method for overcoming particle degeneracy, the main limitation of particle filtering. In PFL, particles are migrated towards regions of high likelihood based on the solution of a partial differential…

Signal Processing · Electrical Eng. & Systems 2024-12-16 Wenyu Zhang , Mohammad J. Khojasteh , Nikolay A. Atanasov , Florian Meyer

The dynamic properties of fluid, including density, surface tension, diffusivity and viscosity, are temperature-dependent and can significantly influence the flow dynamics of mesoscopic non-isothermal systems. To capture the correct…

Computational Physics · Physics 2020-07-21 Kaixuan Zhang , Jie Li , Shuo Chen , Yang Liu

The sensitive and reliable in-droplet chemical analysis benefits from the enhanced partition of an analyte into the droplets. This work, we will show that chemical reactions in surface nanodroplets can shift the partition of analytes from a…

Soft Condensed Matter · Physics 2021-10-04 Zixiang Wei , Jae Bem You , Hongbo Zeng , Xuehua Zhang