1. Field
This application relates generally to simulating a fluid flow over a surface and, more specifically, to generating both inviscid and viscous fluid-flow simulations using a quasi-simultaneous technique for a fluid flow over a computer-generated aircraft surface.
2. Description of the Related Art
Aerodynamic analysis of an aircraft moving through a fluid typically requires an accurate prediction of the properties of the fluid surrounding the aircraft. Accurate aerodynamic analysis is particularly important when designing aircraft surfaces, such as the surface of a wing or control surface. Typically, the outer surface of a portion of the aircraft, such as the surface of a wing, is modeled, either physically or by computer model, so that a simulation of the fluid flow can be performed and properties of the simulated fluid flow can be measured. Fluid-flow properties are used to predict the characteristics of the wing including lift, drag, boundary-layer velocity profiles, and pressure distribution. The flow properties may also be used to map laminar and turbulent flow regions near the surface of the wing and to predict the formation of shock waves in transonic and supersonic flow.
A computer-generated simulation can be performed on a computer-generated aircraft surface to simulate the fluid dynamics of a surrounding fluid flow. The geometry of the computer-generated aircraft surface is relatively easy to change and allows for optimization through design iteration or analysis of multiple design alternatives. A computer-generated simulation can also be used to study situations that may be difficult to reproduce using a physical model, such as supersonic flight conditions. A computer-generated simulation also allows a designer to measure or predict fluid-flow properties at virtually any point in the model by direct query, without the difficulties associated with physical instrumentation or data acquisition techniques.
In some cases, a computer-generated simulation includes a computational fluid dynamics (CFD) simulation module used to predict the properties of the fluid flow. A CFD simulation module estimates the properties of a simulated fluid flow by applying a field equation that estimates the interaction between small simulated fluid volumes, also referred to as fluid cells. Because a single CFD simulation module may include millions of individual fluid cells, the complexity of the relationship between fluid cells can have a large effect on the computational efficiency of the simulation. Complex CFD simulation modules can be computationally expensive and require hours or even days to execute using high-performance computer processing hardware.
To reduce the computational burden, in some instances it is desirable to use a CFD simulation module that simplifies the fluid dynamics and produces a fluid simulation that can be solved more rapidly. For example, for fluid flows that are relatively uniform or are located away from an aircraft surface, a simplified simulation that minimizes or ignores certain fluid dynamic phenomena can be used. In the examples discussed below, a simplified simulation may ignore fluid dynamic contributions due to fluid viscosity, which, in some cases, have little effect on the overall behavior of the fluid flow. A simplified simulation that ignores fluid viscosity may be called an inviscid simulation. By using an inviscid simulation to simulate at least part of the fluid flow, processing time may be improved.
In other situations, where the fluid flow is not as uniform, it may be necessary to use a CFD simulation module that is more sophisticated and capable of accurately predicting the fluid properties, using more complex fluid dynamics. In the examples discussed below, a more sophisticated simulation may account for dynamic contributions due to fluid viscosity. A simulation that accounts for fluid viscosity may be called a viscous simulation. Under certain conditions, a viscous simulation may be more accurate, particularly for portions of the fluid flow near the aircraft surface where fluid viscosity affects the results. However, viscous simulations are also likely to require more computing resources and therefore require more time to solve.
It may be advantageous to construct a hybrid computer-generated simulation that employs both an inviscid CFD simulation module in locations where the fluid flow is relatively uniform, and a viscous CFD simulation module in locations where the fluid dynamics are more complex. By combining different CFD simulation modules, a hybrid computer-generated simulation may increase processing speed while producing accurate results.
Using multiple CFD simulation modules may be difficult, particularly if the CFD simulation modules were not configured to work together. The interface between the simulation modules must be constructed so that the resulting computer-generated simulation is both computationally efficient and analytically robust. The techniques described herein solve some of the difficulties in implementing a computer-generated simulation using multiple simulation modules.