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CFD simulations of direct gas injection, especially in large dual-fuel engines, can be expensive both regarding time and computational power. The nozzle area needs to be resolved with a fine mesh to capture all phenomena and for a full engine model this results in a large amount of cells. A method using a Lagrangian Particle Tracking (LPT) approach...
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Citations
... Particle-laden turbulent flows have significant importance in various natural phenomena and industrial processes [1,2]. Lagrangian particle tracking has been adopted in recent studies to simulate respiratory droplets in turbulent flows [3] or internal combustion engines [4,5], ink-jet printing [6] or in-flight ice accretion problems [7][8][9]. ...
... Many natural phenomena and industrial processes involve complex multi-phase flows in which particles and the surrounding fluid exchange mass, momentum, and energy. For instance respiratory droplet in turbulent flows [70,68] or internal combustion engine [69,38], ink-jet printing [36] or in-flight ice accretion problems [71,30]. Other examples are erosion problems in turbomachinery [13] or in wind-turbine blades due to rain [12]. ...
Particle tracking of a dispersed phase within an underlying flow field is routinely used to analyse both industrial processes and natural phenomena. The efficiency of parallel algorithms to simulate fluid-particle systems is strongly influenced by the different evolution of the flow and the particles dynamics. In unsteady simulations, the parallel efficiency is even more critical because the flow solution changes over time. Indeed, a domain partitioning based on particle workload is possibly sub-optimal in terms of the number of fluid volume elements associated to each process. An efficient mesh partitioning based on graph representation is implemented. It can handle unstructured hybrid meshes composed by triangles and quadrilaterals in two spatial dimensions, and by tetrahedra, hexahedra, prisms, and pyramids in three dimensions. In order to obtain a domain decomposition to efficiently follow the particle trajectories, a preliminary solution is computed to suitably tag the fluid domain cells. The obtained weights represent the element probabilities to be crossed by particles and are used by the load-balancing algorithm to partition the mesh. Another challenging aspect of a scalable implementation is the initial particle location due to the arbitrary shapes of each subdomain. An innovative parallel raytracing particle location algorithm is presented. It takes advantage of a global identifier for each particle, resulting in a significant reduction of the overall communication among processes. In addition, the parallel particle evolution and collection efficiency computation are described. The proposed approach is tested against reference cases for the coupled flow-particle simulation of ice accretion over 2D and 3D geometries. Two different cloud droplet impact testcases have been simulated: a NACA 0012 wing section and a NACA 64A008swept horizontal tail. Furthermore, a cloud droplet impact test case starting from an unsteady flow around a 3D cylinder has been simulated to evaluate the code performances.
... Fluid-particle systems are present in many applications ranging from natural phenomena to industrial processes. Recent studies adopted Lagrangian particle tracking to simulate respiratory droplet in turbulent flows [1] or internal combustion engine [2,3], ink-jet printing [4] or in-flight ice accretion problems [5,6]. In a Lagrangian particle tracking algorithm, the solution accuracy is proportional to the number of sample particles. ...
Coupled fluid-particle simulations are routinely used in a variety of applications, ranging from respiratory droplet spreading to internal combustion engines, from ink-jet printing to in-flight ice accretion. The efficiency of parallel algorithms to simulate fluid-particle systems is strongly influenced by the different evolution of the flow and the particles dynamics. Indeed, a domain partitioning based on particle workload is possibly sub-optimal in terms of the number of fluid volume elements associated to each process. In this work, an efficient mesh partitioning based on graph representation is implemented. It can handle unstructured hybrid meshes composed by triangles and quadrilaterals in two spatial dimensions, and by tetrahedra, hexahedra, prisms, and pyramids in three dimensions. In order to obtain a domain decomposition to efficiently follow the particle trajectories, a preliminary solution is computed to suitably tag the fluid domain cells. The obtained weights represent the element probabilities to be crossed by particles. The algorithm is implemented using MPI distribute memory environment. The proposed approach is tested against reference cases for the coupled flow-particle simulation of ice accretion over 2D and 3D geometries. Two different cloud droplet impact test cases have been simulated: a NACA 0012 wing section and a NACA 64A008 swept horizontal tail. The computed collection efficiency compares fairly well with reference numerical and experimental data. The parallel efficiency of the algorithm is verified on a distributed memory cluster.
