SummaryIn Lagrangian particle‐based methods such as smoothed particle hydrodynamics (SPH), computing totally divergence‐free velocity field in a flow domain with the smallest error possible is the most critical issue, which might be achieved through solving pressure Poisson equation implicitly with higher particle resolutions. However, implicit solutions are computationally expensive and may be particularly challenging in the solution of multiphase flows with highly nonlinear deformations as well as fluid‐structure interaction problems. Augmented Lagrangian SPH (ALSPH) method is a new alternative algorithm as a prevalent pressure solver where the divergence‐free velocity field is achieved by iterative calculation of velocity and pressure fields. This study investigates the performance of the ALSPH technique by solving a challenging flow problem such as two‐dimensional flow around a cylinder within the Reynolds number range of 50 to 500 in terms of improved robustness, accuracy, and computational efficiency. The same flow conditions are also simulated using the conventional weakly compressible SPH (WCSPH) method. The results of ALSPH and WCSPH solutions are not only compared in terms of numerical validation/verification studies, but also rigorous investigations are performed for all related physical flow characteristics, namely, hydrodynamic coefficients, frequency domain analyses, and velocity divergence fields.

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This article proposes a novel graphics processing unit‐based active nematic flow solver based on the smoothed particle hydrodynamics (SPH) method. Nematohydrodynamics equations are discretized using the SPH algorithm. Flow behavior, nematic ordering, topological defects, and vorticity correlation are calculated and discussed in detail. The spectrum of the kinetic energy with respect to the wavenumber is calculated at high particle resolution, and its slope at the different length scales is discussed. To exploit the SPH capabilities, pathlines of nematic particles are evaluated during the simulation. Finally, the mixing behavior of the active nematics is calculated as well and described qualitatively. The effects of two important parameters, namely, activity and elastic constant are investigated. It is shown that the activity intensifies the chaotic mixing nature of the active nematics, while the elastic constant behaves oppositely.

This paper proposes a novel active nematic flow solver based on the particle based Langrangian smoothed particle hydrodynamics (SPH) method accelerated on the CUDA platform. Nematohydrodynamics equations are discretized using the SPH algorithm, and the periodic domain is enforced using the periodic ghost boundary condition. Flow behavior, nematic ordering, topological defects, velocity and vorticity correlations are calculated and discussed in detail. Due to the high particle resolution, the spectrum of the kinetic energy with respect to the wavenumber is calculated, and universal relation is observed for the nematic flow. To exploit the SPH capabilities, pathlines of nematic particles are evaluated during the simulation. Finally, the mixing behavior of the active nematics is calculated as well and described qualitatively. The effects of two important parameters, namely, activity and elastic constant are investigated. It is shown that the activity intensifies the chaotic nature of the active nematic by increasing the pathline and mixing efficiency, while the elastic constant behaves oppositely.