This program simulates a freezer that has a few different kinds of normal and anomalous behavior. The simulator is implemented by having a micro-simulator that emulates the physics of a freezer. The simulator has physical state variables (current temperature right now) and external control variables (power available, door open, door slightly open).
Various parameters of the simulation such as output temperature scale (Farhenheit or Celsius), output format, time step and other aspects can be customized from the command line.
See https://github.com/tdunning/freezer/wiki/Sample-Output for some sample output.
To compile the simulator simply do
mvn package
This will create the stand-alone executable target/freezer which you can run directly on any
machine with Java 1.7 or better.
The program accepts the following command line options
-output output-file-name - sets the output file name. Use - to direct output to standard out (the default).
-fahrenheit - sets the output temperature scale to Fahrenheit. The default is to use Celsius.
-time - sets the duration of the simulation. The simulation will start on July 1, 2015 and will extend for as long as you like. For convenience, you can use m, h, d or w to indicate units of minutes, hours, days or weeks. The default unit is seconds.
-format - sets the output format. You can pick from CSV (default), TSV, JSON or JSON_LINE. JSON wraps the entire output
in a JSON list while JSON_LINE outputs individual JSON structures each on a line. Pick JSON if you are pedantic about the
output file containing strictly correct JSON, pick JSON_LINE for most other uses.
-dt - sets the time stamp on the output. Default is 5 seconds, but if you want to see the control actions of the temperature controller you might want to set it down to 0.25 seconds. Many of the faults can be as short as tens of
seconds so you probably don't want to set this too high. Setting it larger produces less output and thus makes the
simulator run faster.
The controlling variables are simulated by taking the union of several discrete state machines. Each of these state machines generates transition events according to a simple Markov model. The current state of each of these machines defines the parameters of the physical simulation.
The external power system states are:
NORMAL_POWER - externalPower is 1, transition to POWER_FAIL is exponential time distribution
with mean of months.
POWER_FAIL - externalPower is 0, transition to NORMAL_POWER is mixed exponential with
means of 1 minute and 2 hours. 90% of transitions are quick.
The door state machine has the following states:
CLOSED - thermal coupling to outside world is very low. Transition to OPEN is exponential with a rate that depends on time of day. When the door is closed, there is a very small chance that it isn't actually closed, but is left in the previous state until the next time the door is opened. OPEN - thermal coupling to outside world is very high. The door stays open for a time uniformly distributed between 10 and 30 seconds and then transitions to either CLOSED (98%) or LEAK (2%). LEAK - thermal coupling to outside world is low, but not terribly so. Transition to open is same as transition from CLOSED.
Here is a state diagram:
The physical model involves a compressor that turns on if the temperature is > TEMP_MAX and the door state is CLOSED or LEAK. The compressor turns off if the temperature is <TEMP_MIN.
The compressor when on is modeled as a very cold heat sink coupled to the freezer. The environment is modeled as a heat source coupled to the freezer. A simple implementation of Newton's law is used to compute the freezer temperature over time. The DOOR state controls the thermal coupling to the outside world and the POWER state controls whether the compressor actually does any good.
The discrete time simulator maintains a priority queue of upcoming events. To advance, an event
is popped off the queue, time is moved to the time of that event and the run() method is called
on that event. In most cases, this causes new events to be scheduled.
This simulator is very simple, but fairly effective and easy to program. There are three methods for the simulator
schedule - allows new events to be scheduled in the future
step - advances the simulation to the next event in the schedule
nextTransition - returns the time of the next event to be processed without changing that event. This
allows other processing up to that time to be done.
Between events the temperature is modeled using a closed form solution of Newton's equation for heat transfer.
Here is some sample output. You can see where somebody left the door open.
