XFlow – Fluid Simulation | Adaptive Corp

IMPROVING PRODUCT PERFORMANCE WITH FLUIDS SIMULATIONS

In today’s marketplace, the process of updating or developing new products is increasingly challenging. Product innovators must walk a fine line between consumer wants and needs, development and production costs, and point-of-sale pricing. Manufacturers rely upon simulations to save time and money—and more and more, they’re demanding even greater complexity in simulation scenarios, especially real-world behavior under extreme conditions, such as critical flight maneuvers, powertrain lubrication, and vehicles wading.

Fortunately for 3DEXPERIENCE users, SIMULIA Fluids Simulation portfolio includes XFlow with particle-based Lattice-Boltzmann technology for high fidelity computational fluid dynamics (CFD).

Thanks to XFlow’s state-of-the-art technology, users can handle complex CFD workflows involving free-surface flows, complex multiphase flows, fluid-structure interactions, and high-frequency transient simulations with real moving geometries. XFlow’s automatic lattice generation and adaptive refinement technologies reduce inputs, which helps users minimize time and effort in the meshing and pre-processing phase—meaning engineers can concentrate more of their effort on iterating and optimizing designs.

In addition, surface complexity isn’t a limiting factor, due to XFlow’s discretization approach, because users can control the underlying lattice with a small set of parameters. The lattice adapts to the presence of moving parts and is tolerant to the quality of the input geometry. To gain greater insight into flow and thermal performance, XFlow’s advanced rendering features provide realistic visualization. The product’s unique capabilities mean companies can reduce physical testing while also making more informed, better decisions more quickly.

Three complementary technologies form the core of SIMULIA Fluids Simulation portfolio, combining to offer customers scalable fluids simulation tools that handle a wide range of real-world applications. Dassault Systèmes is committed to enhancing and expanding its Fluids Simulation portfolio through its SIMULIA brand in order to provide end-to-end solutions for a broad range of industry processes on the 3DEXPERIENCE platform.

More Information
> XFlow Brochure
> XFlow Datasheet

Unique CFD Approach

In non-equilibrium statistical mechanics, the Boltzmann equation describes the behavior of a gas modeled at mesoscopic scale. The Boltzmann equation is able to reproduce the hydrodynamic limit but can also model rarified media with applications to aerospace, microfluidics or even near vacuum conditions. As opposed to standard MRT, the scattering operator in XFlow is implemented in central moment space, naturally improving the Galilean invariance, the accuracy and the stability of the code.

XFlow includes an innovative, particle-based kinetic algorithm, specifically designed to perform quickly with accessible hardware. This discretization approach removes the limitations of surface complexity and avoids the classic domain-meshing process. The level of detail of the underlying lattice can be easily controlled by users with a small set of parameters. The lattice is also tolerant to the quality of the input geometry, and it adapts to the presence of moving parts.

The resolved scales are automatically adapted to user requirements in the XFlow engine, refining the solution’s quality near the walls, dynamically adapting to the presence of strong gradients, and refining the wake as the flow develops.

The highest-fidelity Wall-Modeled Large Eddy Simulation (WMLES) approach to turbulence modeling available is found in XFlow. The foundational, state-of-the-art LES, based on the Wall-Adapting Local Eddy (WALE), offers a consistent local eddy viscosity and near-wall behavior, as well as CPU-times similar to most codes providing only RANS analysis. XFlow models the boundary layer with a unified, non-equilibrium wall function, which works in most cases—therefore the user doesn’t need to choose between various models and define limitations for each approach.