SPH-flow Explorer: Bring design forward with earlier results
The SPH-flow solvers use the Smoothed Particle Hydrodynamics (SPH) method. This method looks at computational fluid dynamics in a new light. SPH-flow Explorer is made to simulate complex problems faster than ever before.
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SPH-flow Explorer: shortest time-to-results than ever
SPH-flow Explorer is a brand-new solver optimized to deliver results as fast as possible. It relies on finely tuned High-Performance Computing (HPC) capabilities, involving vectorization, MPI multi-CPU communications and, in a near future, OpenMP multi-threading and GPGPU technologies. SPH-flow Explorer can be 5 to 100 times faster than conventional Finite Volume (FV) solvers on applications that best fit with the SPH method, meaning that 1 week of computation may now shrink to few hours, with often better simulation results compared to FV on such applications.
Features
No tedious meshing operations for faster and easier simulation setup
Lagrangian formulation for advection-related physical phenomena
Accurate free-surface tracking

Wide variety of accounted physics

Strongly scalable MPI algorithms for HPC

No tedious meshing operations for faster and easier simulation setup
The meshing procedure in most conventional solvers – especially structured ones – is both delicate and time-consuming. It often represents a significant portion of engineering time.
Conversely, the SPH-flow solvers do not require any user meshing operation. Its particle generator automatically populates the simulation domain.
More information about this feature on page Research Fast and accurate SPH modelling of 3D complex wall boundaries in viscous and non-viscous flows

Lagrangian formulation for advection-related physical phenomena
The SPH method is based on a Lagrangian formulation: the flow is described by means of discrete particles which move with the fluid. Under such formulation, the advection term of the Navier-Stokes equations vanishes. This constitutes a substantial benefit, when one considers the challenge that accurate and robust computation poses for Eulerian-based solvers.
The SPH-flow solvers show full advantage of this strength when simulating flows driven by advection-related physical phenomena.

Accurate free-surface tracking
Many design problems involve fluids whose domains are not known in advance. Those flows may deal with surface deformation, such as waves, or fragmentation and coalescence, such as droplet formation and merging.
Thanks to its Lagrangian nature, the SPH-flow solvers implicitly track the free surfaces. No approximate, diffusing nor processor-consuming numerical computation is needed to accurately locate the interfaces.

Wide variety of accounted physics
The SPH-flow solvers can account for many physical models: viscosity, compressibility, thermal, surface tension, contact angle, non-Newtonian fluids… Different implementations have been used for most of them. From this complete set of numerical alternatives, the SPH-flow solvers exhibit a selection of effective, application-specific guidelines.

Strongly scalable MPI algorithms for HPC
Because millions of particles may be necessary to simulate most industrial applications, SPH-flow Explorer parallel computing performance has been optimized to an advanced level, involving vectorization, MPI multi-CPU communications and, in a near future, OpenMP multi-threading and GPGPU technologies. Clear scalability has been proven on up to tens of thousands of processors.
Such HPC results make it possible to simulate complex and realistic problems with relevant accuracy and at an affordable computation cost.
More information about this feature on page Research On distributed memory MPI-based parallelization of SPH codes in massive HPC context

Characteristics
Resolved physics:
- Navier-Stokes or Euler equations
- Incompressible approach
- Implicitly tracked free surface
- Viscosity models
- Surface tension models
- Heat transfer and thermal analysis
- Various boundary conditions: no-slip/slip, inlet/outlet…
- Rigid body with imposed or free motion
Numerical aspects:
- Particles-based method SPH
- Lagrangian approach
- Pressure Poisson Equation (PPE) resolution
- Ghost boundary formulations
- Implicit time scheme
- Scalable parallel computing based on MPI protocol