Introduction

Note

This document is a methodology guide – its main purpose is to expose readers to the capabilities of Simcenter Amesim in the domain of co-simulation with CFD software. As these capabilities do not rely on a feature set specifically created for the purposes of co-simulation with CFD software, it cannot be thought of as a user guide. It does, however, provide the user with a view into the possible applications and benefits which can be extracted from 1D/3D CFD co-simulation, as well as providing readers with insights as to how this can be achieved.

Industry today is becoming more and more reliant upon simulation, which has become an intrinsic part of the toolkit for companies attempting to increase the efficiency of their processes and the performance of their products. Indeed, numerous parts of the industrial design cycle are incorporating modeling within their methods, which saves both time and money, effectively shortening the design and production cycles.

Figure 1: Simcenter Amesim in relation to other CFD software

The design process of mechatronics systems such as machine tools can be described by the well-known V-Cycle shown below.

Figure 2: The V-Cycle model of system engineering design process

This V-Cycle model is a combination of top-down design steps (the left side of the V) and bottom-up validation steps (the right side of the V). The use of simulation software fits with this V-Cycle model. Different levels of modeling are needed to cover the different steps of the design process. In fact, 4 levels of modeling are typically defined depending on their use during the design process:

Schematic representation	Modelling approach
	Functional Level Description of system functions and system states Example: Petri Net
	Signal Level Control modeling including simplified model of physical Components Example: Block Diagram
	System Level Detailed modeling of physical components which cover different physical domains. A dynamic model of the whole system is available at this level which is also called physical system modeling. Example : 1D Gearbox Simulation
	Geometric level The detailed geometry of a component is sized or optimized at this level. Example: 3D CFD simulation

The modeling level which is the most suited for simulating the whole system by describing the power exchanges between components and which is well suited for system design, and for control design, is the System level.

This level of modeling is versatile, so it is able to cover different physical domains and different applications. The theoretical frame of this system modeling level is Bond Graph theory. The modeling approach regards the power exchanges between components while respecting the balance equations of physics. This modeling approach is based on connection of elementary models by using power links. This method, which is the called multiport approach, makes it possible to associate different modeling assumptions at the same graphical representation, which affords good representation of the technology. The mathematical associated model has the form of ODEs (Ordinary Differential Equations) or DAEs (Differential Algebraic Equation).

The Signal level which is based on a block diagram approach is still probably the most popular for system modeling, especially for control design. However, even if it is possible to describe a whole system by assembling specific sets of equations, it becomes challenging to develop models of complex systems with this approach due to the model’s lack of a defined architecture and standard connection rules.

Figure 3: Comparison of the Signal vs System levels - Model of an Electro-Hydraulic Actuator

The Geometric Level is well adapted when looking for detailed results on a specific part of a system. But it is very CPU-time consuming (hours to days for 1 run), which makes it impractical to model a complete system with all its parts included to get its energy efficiency:

Figure 4: Comparison of the Geometric vs System levels – Model of a Piping system

Another difficulty with the Geometric level when used in a more global context is to sum all the elementary values on each cell with its 3D orientation to get the appropriate generalized value. To access power or energy, this heavy post-processing has to be done twice, with effort and flow variables to be post-processed.

As 1D modeling does not take the 3D geometrical aspects of a system into account, it is only natural that geometry-dependent physical phenomena can sometimes be difficult to account for. On the other end of that spectrum lies modeling which is predominantly geometry-based, and specifically Computational Fluid Dynamics (CFD) in the context of fluid flows. Complex flow phenomena can be accurately simulated and designed-for using this type of software package.

As a result, 1D/3D coupling is often used, as it provides more precise results at a fraction of the cost, very early on in the design process. This approach also has the significant advantage of rendering it possible to incorporate systems from different physical domains into a single study. Thus, it is possible to obtain meaningful information about the complex dynamics which may arise due to such couplings.