Before diving into some examples, there is a bit of background
required in order to understand what a
connector in Modelica is,
why it is used and the mathematical basis for their formulations.
We’ll cover these points first before proceeding.
So far, we’ve talked primarily about how to model behavior. What we’ve seen so far are models composed largely of textual equations. But from this point forward, we will be exploring how to create reusable component models. So instead of writing Ohm’s law whenever we wish to model a resistor, we’ll instead add an instance of a resistor component model to our system.
Until now, the models that we’ve shown have all been self contained. All the behavior of our entire system was captured in a single model and represented by textual equations. But this approach does not scale well. What we really want is the ability to create reusable component models.
But before we can dive into how to create these components, we need to
first discuss how we will be connecting them together. The component
models that we will be building during the remainder of the book are
still represented by a
model definition. What sets them apart
from the models we have seen so far is that they will feature
connector is a way for one model to exchange information with
another model. As we’ll see, there are different ways that we may
wish to exchange this information and this chapter will focus on
explaining the various semantics that can be used to describe
connectors in Modelica.
In order to understand one specific class of connector semantics, it is first necessary to understand a bit more about acausal formulations of physical systems. An acausal approach to physical modeling identifies two distinct classes of variables.
The first class of variables we will discuss are “across” variables (also called potential or effort variables). Differences in the values of across variables across a component are what trigger components to react. Typical examples of across variables, that we will be discussing shortly, are temperature, voltage and pressure. Differences in these quantities typically lead to dynamic behavior in the system.
The second class of variables we will discuss are “through” variables (also called flow variables). Flow variables normally represent the flow of some conserved quantity like mass, momentum, energy, charge, etc. These flows are usually the result of some difference in the across variables across a component model. For example, current flowing through a resistor is in response to a voltage difference across the two sides of the resistor. As we will see in many of the examples to come, there are many different types of relationships between the through and across variables (Ohm’s law being just one of many).
It is extremely important to know that Modelica follows a convention that a positive value for a through variable represents flow of the conserved quantity into a component. We’ll repeat this convention several times later in the book (especially once we begin our discussion of how to build models of Components).
The next section will define through and across variables for a number of basic engineering domains.