Technology Overview

CFD Modeling and Simulation Technology Overview

The SIMULIA PowerFLOW® CFD solution is built on our proprietary DIGITAL PHYSICS technology based on an extended implementation of the Lattice Boltzmann Method (LBM) that we have developed over two decades. PowerFLOW differs from competing RANS-based Computational Fluid Dynamics (CFD) technology in fundamental ways that make our simulations more useful to our customers.


  • Inherently transient: Simulate time-dependent phenomena such as turbulent flows;
  • Numerically stable: Reliable even when used to analyze complex geometries; and
  • Highly accurate.

The traditional approach in CFD modeling has been to start with Navier-Stokes equations, which are a set of partial differential equations that describe the behavior of a fluid. These equations are theoretically sound for many types of flows but are very complex and highly non-linear. Because these equations by their nature can only be directly solved for the simplest scenarios, their application in practice requires the use of numerical techniques to approximate a solution. The main drawbacks of the traditional CFD approach therefore lie not with the Navier-Stokes equations themselves but in the numerical techniques that must be deployed to solve them.

In the traditional CFD approach, the continuous Navier-Stokes equations are discretized, meaning that the flow field is broken up into discrete cells located in three-dimensional space (analogous to the two-dimensional pixels on a computer screen), where flow properties such as velocity and pressure are solved. Because solving for the fluid properties at all locations in time and space is not mathematically possible, values are computed at these discrete locations, which makes up what is referred to as "the computational grid."

There are also significant difficulties with these numerical techniques when simulating flow conditions at the interface where the fluid grid meets a surface. The necessary calculations are computationally intensive and often become unstable, meaning that no pertinent solution can be provided. In order to address these difficulties and reduce the computational costs, many traditional CFD approaches use a steady-state solver that simplifies the problem by calculating an average value for each discrete cell rather than predicting the changing values in time. To improve robustness and stability, traditional approaches introduce excess numerical dissipation that, while improving stability, works to destroy subtle flow structures that are critical for accuracy.

In contrast, our DIGITAL PHYSICS technology, based on the Lattice Boltzmann Method, describes the fluid flow at the mesoscopic level, between the molecular and continuum levels of Navier-Stokes. In addition to applications of traditional solvers, the Lattice Boltzmann Method also discretizes the flow domain. In spite of this discretization, it was proved in the early 1990s that the Lattice Boltzmann Method accurately provides CFD solutions equivalent to the highly non-linear Navier-Stokes equations without actually having to solve them. This theoretical proof was the genesis of PowerFLOW.

PowerFLOW provides a further advantage in that it can handle fully complex surface geometry, of which the details are equally important to generate accurate simulation predictions. Another unique component of our core technology is the "discretizer," which automatically determines the fluid/surface intersection without compromising the geometric fidelity. Other CFD technologies offer automatic mesh generation but the limitations of their solvers require that the geometry be simplified, often to such an extent that the accuracy of the results is compromised.

In contrast to traditional CFD approaches, PowerFLOW's extremely low numerical dissipation allows for accurate simulation of time-dependent flows, enabling sensitive applications such as aeroacoustics. Furthermore, PowerFLOW has been proven to be highly scalable on massively parallel computers to enable shorter turn-around times, which is a very challenging task with traditional CFD solvers.

For strongly turbulent flows, it is not computationally practical to perform direct simulations by resolving all of the scales of motion – from the microscopic ones to large-scale flow structures that are the size of the vehicle. Thus, it becomes necessary to incorporate models to account for these unresolved turbulent flow structures. The small turbulent scales are universal in nature and can be predicted with theoretical models. The large scales of turbulence are not universal, and no model exists that can be relied upon to accurately predict their behavior.

The most common approach to this problem in CFD is to rely on turbulence modeling across the entire scales of turbulence. These models extend far beyond their theoretical basis and are often applied to steady-state solutions where the time-dependent nature of the flow is completely ignored. Due to the non-universal nature of the large turbulent scales, this approach has led to a range of user-selected turbulence models with empirical tuning of the parameters in an attempt to be suitable for a specific class of flows. These compromises have enabled traditional CFD approaches to be tailored to specific applications and deployed in a way that provides some level of insight and understanding of flow behaviors. However, the compromises limit the accuracy of these models, along with their ability to replace the complex experimental testing required to ensure that designs meet their targets.

PowerFLOW is a transient solver with high three-dimensional resolution and low dissipation. This allows PowerFLOW to directly simulate the large unpredictable turbulent scales. PowerFLOW uses turbulence theory to model only where it is valid and directly simulates the rest.

These combined attributes of PowerFLOW's underlying technology enable us to bring simulation solutions to new levels of accuracy and robustness. This, in turn, enables our customers to improve their design development processes from requiring physical prototype testing at every stage by substituting robust, detailed and accurate digital CFD modeling simulations and allowing the final physical prototype stage to be one of confirmation rather than discovery.

For more information or to see our simulation software in action, visit the Resource Library to watch recent demos and interviews with our experts.