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Computational Approaches to Polymeric Nanocomposites
Published in Sefiu Adekunle Bello, Hybrid Polymeric Nanocomposites from Agricultural Waste, 2023
Saheed Olalekan Ojo, Sikiru Oluwarotimi Ismail
Dissipative particle dynamics (DPD) is a particle-based method, such as the MD and BD techniques, and is suitable for both Newtonian and non-Newtonian fluids on microscopic length and time scales. The basic unit of DPD is a molecular assembly (representing a particle) that is characterised by its mass, mi, position, ri, and momentum, μi. The force describing the interactions between two DPD particles may be expressed as a sum of the conservative, FijC, dissipative, FijD, and random, FijR, forces in Equation (5.57) [2]. Fij=FijC+FijD+FijR,
Investigation on the formation and stability of microemulsions with Gemini surfactants: DPD simulation
Published in Journal of Dispersion Science and Technology, 2023
Haixia Zhang, Zhenxing Zhu, Zongxu Wu, Fang Wang, Bin Xu, Shoulong Wang, Lijuan Zhang
Dissipative Particle Dynamics theory (DPD) is a mesoscopic-level simulation method in which the aggregates of several atoms or molecules are defined as a bead.[45] To simplify the calculations, the physical quantities in the DPD simulation were reduced units, and all beads had the same mass, length, and time scales. Every two particles i and j in a system interact with each other through a pairwise, two-body, short-ranged force fij is made up of a conservative force FijC, a random force, FijR and a dissipative force, FijD.
Development of a novel hybrid method combining finite difference method and dissipative particle dynamics to simulate thrombus formation on orifice flow
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2020
Dissipative particle dynamics (DPD) is a mesoscopic method for simulating the dynamic properties of fluid. The DPD system involves a set of particles moving in continuous space and discrete time. In DPD, the fluid and solid objects are represented as a collection of interacting points, each representing a group of atoms or molecules. In our previous work (Yi and Tamagawa 2018), thrombus formation on orifice flows was simulated by DPD. In the paper, platelet aggregation was computed. Thrombus is predicted to form around the reattachment point because the number of aggregated platelets around this point is high.