# Getting Physical¶

Although the previous section got us started with representing
mathematical behavior, it doesn’t convey any connection to *physical*
behavior. In this section, we’ll explore how to build models that
represent the modeling of physical behavior. Along the way, we will
highlight some of the language features we can leverage that will not
only tie these models to physical and engineering domains, but, as we
shall see, they can even help us avoid mistakes.

Let’s start with the following example:

```
model NewtonCooling "An example of Newton's law of cooling"
parameter Real T_inf "Ambient temperature";
parameter Real T0 "Initial temperature";
parameter Real h "Convective cooling coefficient";
parameter Real A "Surface area";
parameter Real m "Mass of thermal capacitance";
parameter Real c_p "Specific heat";
Real T "Temperature";
initial equation
T = T0 "Specify initial value for T";
equation
m*c_p*der(T) = h*A*(T_inf-T) "Newton's law of cooling";
end NewtonCooling;
```

As we saw in the examples in our discussion of Simple First Order System, the
previous example consists of a `model`

definition that includes
variables and equations.

However, this time we see the word `parameter`

for the first time.
Generally speaking, the `parameter`

keyword is used to indicate
variables whose value is known *a priori* (*i.e.*, prior to the
simulation). More precisely, `parameter`

is a keyword that
specifies the *variability* of a variable. This will be discussed
more thoroughly in the section on Variability. But for now, we
can think of a `parameter`

as a variable whose value we must
provide.

Looking at our `NewtonCooling`

example, we see there are five
parameters: `T_inf`

, `T0`

, `h`

, `A`

, `m`

and `c_p`

. We
don’t need to bother explaining what these variables are because the
model itself includes a descriptive string for each one. At the
moment, there are no values for these parameters, but we will return
to that topic shortly. As with all the variables we have seen so far,
these are all of type `Real`

.

Let’s examine the rest of this model. The next variable is `T`

(also a `Real`

). Since this variable doesn’t have the `parameter`

qualifier, its value is determined by the equations in the model.

Next we see the two `equation`

sections. The first is an ```
initial
equation
```

section which specifies how the variable `T`

should be
initialized. It should be pretty clear that the initial value for
`T`

is going to be whatever value was given (by us) for the
parameter `T0`

.

The other equation is the differential equation that governs the
behavior of `T`

. Mathematically, we could express this equation as:

but in Modelica, we write it as:

```
m*c_p*der(T) = h*A*(T_inf-T)
```

Note that this is really no different from the equation we saw in our
`FirstOrder`

model from the Simple First Order System example.

One thing worth noting is that the equation in our `NewtonCooling`

example contains an **expression** on the left hand side. In
Modelica, it is **not** necessary for each equation to be an explicit
equation for a single variable. An equation can contain arbitrary
expressions on either side of the equals sign. It is the compiler’s
job to determine how to use these equations to solve for the variables
contained in the equations.

Another thing that distinguishes our `NewtonCooling`

example from
the `FirstOrder`

model is that we can independently adjust the
different parameter values. Furthermore, these parameter values are
tied to physical, measurable properties of the materials or
environmental conditions. In other words, this version is slightly
more physical than the simple mathematical relationship used in the
`FirstOrder`

model because it is related to physical properties.

Now, we can’t really run the `NewtonCooling`

model as is because it
lacks *values* for the six parameters. In order to create a model
that is ready to be simulated, we need to provide those values,
*e.g.*,

```
model NewtonCoolingWithDefaults "Cooling example with default parameter values"
parameter Real T_inf=25 "Ambient temperature";
parameter Real T0=90 "Initial temperature";
parameter Real h=0.7 "Convective cooling coefficient";
parameter Real A=1.0 "Surface area";
parameter Real m=0.1 "Mass of thermal capacitance";
parameter Real c_p=1.2 "Specific heat";
Real T "Temperature";
initial equation
T = T0 "Specify initial value for T";
equation
m*c_p*der(T) = h*A*(T_inf-T) "Newton's law of cooling";
end NewtonCoolingWithDefaults;
```

The only real difference here is that each of the `parameter`

variables now has a value specified. One way to think about the
`NewtonCooling`

model is that we could not simulate it because it
had 7 variables (total) and only one equation (see the section on
Initialization for an explanation of why the ```
initial
equation
```

doesn’t really count). However, the
`NewtonCoolingWithDefaults`

model has, conceptually speaking, 7
equations (6 of them coming from specifying the values of the
`parameter`

variables + one in the equation section) and 7 unknowns.

If we simulate the `NewtonCoolingWithDefaults`

model, we get the
following solution for `T`

.

## Physical Units¶

As mentioned already in this section, these examples are a bit more
physical because they include individual physical parameters that
correspond to individual properties of our real world system.
However, we are still missing something. Although these variables
represent physical quantities like temperature, mass, *etc.*, we
haven’t explicitly given them any physical types.

As you may have already guessed, the variable `T`

is a temperature.
This is made clear in the descriptive text associated with the
variable. Furthermore, it doesn’t take a very deep analysis of our
previous model to determine that `T0`

and `T_inf`

must also be
temperatures.

But what about the other variables like `h`

or `A`

? What do they
represent? Even more important, are the equations **physically
consistent**? By physically consistent, we mean that both sides of
the equations have the same physical units (*e.g.*, temperature,
mass, power).

We could convey the physical units of the different variables more rigorously by actually including them in the variable declarations, like so:

```
model NewtonCoolingWithUnits "Cooling example with physical units"
parameter Real T_inf(unit="K")=298.15 "Ambient temperature";
parameter Real T0(unit="K")=363.15 "Initial temperature";
parameter Real h(unit="W/(m2.K)")=0.7 "Convective cooling coefficient";
parameter Real A(unit="m2")=1.0 "Surface area";
parameter Real m(unit="kg")=0.1 "Mass of thermal capacitance";
parameter Real c_p(unit="J/(K.kg)")=1.2 "Specific heat";
Real T(unit="K") "Temperature";
initial equation
T = T0 "Specify initial value for T";
equation
m*c_p*der(T) = h*A*(T_inf-T) "Newton's law of cooling";
end NewtonCoolingWithUnits;
```

Note that each of the variable declarations now includes the text
`(unit="...")`

to associate a physical unit with the variable. What
this additional text does is specify a value for the `unit`

attribute
associated with the variable. Attributes are special properties that
each variable has. The set of attributes a variable can have depends
on the type of the variable (this is discussed in more detail in the
upcoming section on Variables).

At first glance, it may not seem obvious why specifying the unit
attribute (*e.g.*, `(unit="K")`

) is any better than simply adding
`"Temperature"`

to the descriptive string following the variable.
In fact, one might even argue it is worse because “Temperature” is
more descriptive than just a single letter like “K”.

However, setting the `unit`

attribute is actually a more formal
approach for two reasons. The first reason is that the Modelica
specification defines relationships for all the standard SI unit
attributes (*e.g.*, `K`

, `kg`

, `m`

). This includes complex unit
types that can be composed of other base units (*e.g.*, `N`

).

The other reason is that the Modelica specification also defines rules
for how to compute the units of complex mathematical expressions. In
this way, the Modelica specification defines everything that is
necessary to **unit check** Modelica models for errors or physical
inconsistencies. This is a big win for model developers because
adding units not only makes the models clearer, it provides better
diagnostics in the case of errors.

## Physical Types¶

But truth be told, there is one drawback of the code for our
`NewtonCoolingWithUnits`

example and that is that we have to repeat
the `unit`

attribute specification for every variable. Furthermore,
as mentioned previously, `K`

isn’t nearly as descriptive as
“Temperature”.

Fortunately, we have a simple solution to both problems because
Modelica allows us to define *derived types*. So far, all the
variables we have declared have been of type `Real`

. The problem
with `Real`

is that it could be anything (*e.g.*, a voltage, a
current, a temperature). What we’d like to do is narrow things down a
bit. This is where derived types come in. To see how to define
derived types and then use them in declarations, consider the
following example:

```
model NewtonCoolingWithTypes "Cooling example with physical types"
// Types
type Temperature=Real(unit="K", min=0);
type ConvectionCoefficient=Real(unit="W/(m2.K)", min=0);
type Area=Real(unit="m2", min=0);
type Mass=Real(unit="kg", min=0);
type SpecificHeat=Real(unit="J/(K.kg)", min=0);
// Parameters
parameter Temperature T_inf=298.15 "Ambient temperature";
parameter Temperature T0=363.15 "Initial temperature";
parameter ConvectionCoefficient h=0.7 "Convective cooling coefficient";
parameter Area A=1.0 "Surface area";
parameter Mass m=0.1 "Mass of thermal capacitance";
parameter SpecificHeat c_p=1.2 "Specific heat";
// Variables
Temperature T "Temperature";
initial equation
T = T0 "Specify initial value for T";
equation
m*c_p*der(T) = h*A*(T_inf-T) "Newton's law of cooling";
end NewtonCoolingWithTypes;
```

You can read the definition ```
type Temperature=Real(unit="K",
min=0);
```

as “Let us define a new type, `Temperature`

, that is a
specialization of the built-in type `Real`

with physical units of
Kelvin (`K`

) and a minimum possible value of `0`

”.

From this example, we can see that once we define a physical type like
`Temperature`

, we can use it to declare multiple variables (*e.g.*,
`T`

, `T_inf`

and `T0`

) without having to specify the `unit`

or
`min`

attribute for each variable. Also, we get to use the familiar
name `Temperature`

instead of the SI unit, `K`

. You might be
wondering what other attributes are available when creating derived
types. For further discussion, see the section on
Built-In Types.

At this point, you might find the idea of defining `Temperature`

,
`ConvectionCoefficient`

, `SpecificHeat`

and `Mass`

in every
model extremely tedious. It would be, if it were truly necessary.
But don’t worry, there is an easy solution to this as you will see in
a later section where we discuss Importing Physical Types.