Better Fluid Storage

A while back, I posted a prototype fluid storage system with a mechanic for handling breaches in a pressurized system. I thought I’d be clever by storing fluids as a percentage of a defined volume and pressure. For a “simplified” system, it was quite complicated, and fundamentally flawed.

This time, it is straightforward. Keep track of the amounts of each fluid, a total sum, and volume of the container. Pressure is the sum divided by the volume, and the percent of a fluid is its amount divided by the total sum of all fluids.

tank = {
  volume: 200, sum: 300,
  contents: { hydrogen: 200, oxygen: 100 }
}
pressure = tank.sum / tank.volume -- 1.5
percent_hydrogen = tank.contents.hydrogen / tank.sum -- 0.67

Everything needed from a container can be accessed immediately or with a single calculation involving only two variables.

But what about hull breaches?

Fluids vs Mechanical Classes

I realized that I should define fluid containers very narrowly, all they need care about is a small set of numbers, and have a few functions to modify that state. Enter the Breach class.

Breach(fluidA, fluidB, volume)

Specify which fluid containers are interacting and the volume ( I guess technically it should be area) of the breach. Each update cycle moves the pressure difference multiplied by the volume (area) of the breach from the higher pressure container to the lower pressure container.

What about pumps? I have those, with a “volume” and a “rate” modifier to allow you to adjust how fast the pump works. Pumps only work in one direction, but have a function to reverse them.

Want only one fluid to go through..say, a filter? Made that as well. Valves, so that you can adjust flow rate, filter-pump combos for pushing just the right amount of one fluid, and one-way valves to allow pressure to escape but not allow any blowback.

The Flaws

  • Once pressure is equalized, contents do not mix between fluids.
  • All fluids have the same density. This probably isn’t that hard to fix, but is unneeded for my purposes.
  • All fluids mix. This may or may not be harder to fix depending on how it is approached.
  • Temperature isn’t simulated at all. I would love to have heat transfer and heat affecting density, but these details are not necessary for my current project.

The Code

As of publishing this article, I don’t have a library to give you, but I will update it as soon as I do release it. For now, here is where I have the beginnings of a library. No matter what, I can promise it will be available by the end of April (or upon request).

Grammar-Based Generation

To me, this is a new form of procedural generation. You declare specific rules for your desired content, and then a generator runs accordingly. I’ve only seen it used for text, but I’m sure the same technique works for anything. The simplest example is picking a random item from a list, and a slightly more complex version shows the power of defining a grammar:

grammar = {
  "first name": "Anna", "Belle", "John"
  "last name": "Brown", "Jameson", "Williams"
  "full name": "{first name} {last name}"
}

G(grammar, "full name") -- ex: Anna Williams

The syntax above is pseudocode for a generator I am working on. I plan to allow the use of a custom seed along with the generator so that you can do things like have uniquely generated people for a population, where only a lookup number needs to be stored (if you wish to remember a specific person).

It gets even more powerful when you make it possible to define multiple versions of the same grammar and use different ones depending on an object’s properties, and allow inline code within the grammars. Here’s an incomplete example based on my continuing efforts to build space games:

{
  "system name": {
    {
      props: { pulsar: true }
      "PSR {random(1000)}"
    }
    {
      props: { pulsar: false }
      "{Greek letter} {Latin name}"
      "{random(100)} {Latin genitive}"
      "{modern constellation} G{random(1000,9999)}.{random(1000,9999)}"
    }
  }
}

For this example, pulsars would get their traditional “PSR ###” names, while non-pulsars would get names based on differing classification methods.

I’m currently thinking about a game based on Aurora, but massively simplified and playable in-browser. Grammar-based content generation would play a very important role in this, from generating system names (as above) to NPC ship design.

References

Resources that helped me recognize the potential of grammars:


(Normally I would like to publish working code along with these posts, or some other form of useful data, but today we’re looking at a work-in-progress idea without even that much concrete form.)

Simplified Fluid Storage System

One of my game ideas involves constructing 2D spaceships, and the concept of a simplified system for storing fuel, oxygen, water – really any kind of fluid mixture – in storage tanks. Along with this, it allows simulating breaches between containers, hard vacuum, and the pressurized areas of the ship itself!

{ -- a rough approximation of Earth's atmosphere
  pressure: 1
  volume: 4.2e12 -- 4.2 billion km^3
  contents: {
    nitrogen: 0.775
    oxygen: 0.21
    argon: 0.01
    co2: 0.005
  }
}

{ -- hard vacuum
  pressure: 0
  volume: math.huge -- infinity
  -- the contents table will end up containing negative infinity of anything that leaks into the vacuum
}

It all comes down to storing a total pressure and volume per container, and a table of contents as percentages of the total mixture. The total amount of mass in the system can be easily calculated (volume * pressure), as can the amount of any item in the system ( volume * pressure * percent).

Breaches are stored as a reference in the container with a higher pressure, and a size value is added to the container with lower pressure (representing the size of the hole between them).

Limitations

  • Everything has the same density and mixes evenly.
  • There are no states of matter, everything is treated as a gas.
  • Attempting to directly modify the amount of a fluid is prone to floating-point errors it seems, while mixing containers via the breach mechanic is working as expected.

The code was written in MoonScript / Lua and is available here.

My First Ludum Dare (#32)

Grand Theft Papercut

This was the 4th Ludum Dare that I wanted to participate in, and the first where I actually did. I was inspired by my recent discovery of a GameBoy GTA game, and my unconventional weapon (theme) was a deck of cards.

It was also my first time making anything tile-based, and it worked very well for my experience at the time. Even better, it was the first time I had the capability to load and save, and the game was also the map editor for the game. Very much something I’d like to do again sometime.

You can go play the prototype here.

Realistic Star Frequencies/Colors

UPDATE: A much better resource for frequencies of types of stars is on this wiki page for Elite: Dangerous.

I’ve done a lot of research on stellar classification, perhaps too much. Here’s a visual representation (not at all to scale!) of stars by type from O to L.. and L is a brown dwarf, so it’s not technically a “star” per say.

Stars by type, in order: OBAFGKML

And here’s a table of those color values (in percents RGBA):

  O: {0.521, 0.521, 0.996, 1}
  B: {0.701, 0.898, 1, 1}
  A: {1, 1, 1, 1}
  F: {1, 0.996, 0.780, 1}
  G: {0.988, 0.972, 0.250, 1}
  K: {0.905, 0.549, 0.015, 1}
  M: {0.847, 0.011, 0.031, 1}
  L: {0.302, 0.187, 0.177, 1}

As for the frequencies (as in, percent of stars that are a specific type), they have been slightly manipulated (if I am remembering correctly) to make the rarest types a little more common, but are based on my best guesses from research:

  O: 0.00003
  B: 0.13
  A: 0.6
  F: 3
  G: 7.6
  K: 12.1
  M: 76.45
  L: 0.11

A couple last notes:

  • There are two more brown dwarf / substellar mass classifications I could be using (T and Y), but I am not because they are not commonly visible.
  • Because L-type (and T & Y) “stars” are so hard to see, it is entirely possible they could outweigh the existence of other types, but we just can’t see them!

Code to create the image above is available here.