Methods for Modeling 2d Rocket Flight

In summary: You can't just integrate the angle of attack over time.In summary, the author has formulated a method for modeling the flight of a rocket projectile. However, this system leads to a seemingly circular and unresolvable issue. The author tried to solve this issue by iteration, but it did not work correctly. Additionally, the author found that the approximation algorithm is not very accurate.
  • #1
CSteiner
31
0
I've formulated a method for modeling the flight of a rocket projectile. Can anyone read it over and point out any mistakes false assumptions, etc? thanks!
 

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  • #3
According to Newton’s Second Law, the product ma must remain constant.
For every reasonable definition of m and a (which is missing), this is wrong.
Since its acceleration is changing over time
Not necessarily, R does not have to be constant.

##\Delta m## in the integral has a different meaning compared to above, but uses the same symbol.

Air resistance depends on the velocity and the direction of motion, you cannot integrate it like that (with both meanings for integrate).

Why does alpha depend on the position of the rocket?
Thus, this system leads to a seemingly circular and unresolvable issue.
You solved a differential equation before, where is the problem with setting up another?

The iteration does not work like that. It gives something like an arc, but not the correct results.
 
  • #4
Thanks for taking the time to read and reply!

For every reasonable definition of m and a (which is missing), this is wrong.

hmm, you're right. I should have done the derivation purely in terms of momentum.

Not necessarily, R does not have to be constant.

Δm in the integral has a different meaning compared to above, but uses the same symbol.

Air resistance depends on the velocity and the direction of motion, you cannot integrate it like that (with both meanings for integrate).

Why does alpha depend on the position of the rocket?

Well, I was assuming a constant R.

There is no delta m in the integral.

Huh. I guess I just assumed that air resistance was always anti-parallel to direction of motion. I suppose I'll just set the air resistance to be negligible then.

Alpha can depend either on position or on time. Either way its an unknown function.

You solved a differential equation before, where is the problem with setting up another?
The iteration does not work like that. It gives something like an arc, but not the correct results.

I don't know any methods for solving an ODE containing an unknown function (the angle of attack). I tried many ways to get an explicit equation of velocity and angle of attack, but I didn't succeed. I don't believe there is a way to avoid the implicit nature of the system. Thus the approximation algorithm.

Is it too far off to even be an approximation? What if I modified the algorithm to take the average of angle n and angle n-1, like the RK2 method?
 
  • #5
CSteiner said:
Well, I was assuming a constant R.
That assumption should appear somewhere then. For most rockets, it is not true.
CSteiner said:
There is no delta m in the integral.
In the equation with the integral, in the denominator.

CSteiner said:
I guess I just assumed that air resistance was always anti-parallel to direction of motion.
That is a reasonable approximation, but it is unrelated to my point. The acceleration from air resistance is not constant in time, so its contribution to velocity is not proportional to time.
Actually, real rockets have two different directions: direction of motion (relevant for drag) and direction of thrust (relevant for propulsion). Usually they are not so far apart from each other because that optimizes efficiency, but that is another approximation that should be mentioned somewhere.
CSteiner said:
Alpha can depend either on position or on time. Either way its an unknown function.
Sure, but alpha cannot be calculated based on position values relative to the starting point or some other fixed reference.

CSteiner said:
I don't know any methods for solving an ODE containing an unknown function (the angle of attack)
Every differential equation has at least one unknown function. Sure, alpha will couple the two equations for the directions (a realistic treatment of air resistance will do the same) and probably make an analytic solution impossible, but you can get the iteration steps out of this differential equation.

CSteiner said:
Is it too far off to even be an approximation?
In its current version, I would not use it for any predictions. To know "oh well, the rocket will go up and forwards and then fall down again" you don't need calculations, and I don't think it is more precise than that.
 
  • #6
Every differential equation has at least one unknown function. Sure, alpha will couple the two equations for the directions (a realistic treatment of air resistance will do the same) and probably make an analytic solution impossible, but you can get the iteration steps out of this differential equation.

I meant that. What do you mean by the iteration steps though?
 
  • #7
CSteiner said:
I meant that. What do you mean by the iteration steps though?
The same thing as you when you calculate the position in steps of 0.5 seconds.
You'll certainly need the velocity there.
 

FAQ: Methods for Modeling 2d Rocket Flight

1. What are the main methods used for modeling 2d rocket flight?

The main methods used for modeling 2d rocket flight include numerical methods such as Euler's method and Runge-Kutta methods, as well as analytical methods such as the Tsiolkovsky rocket equation and the two-body problem.

2. How accurate are these methods in predicting 2d rocket flight?

The accuracy of these methods depends on various factors such as the complexity of the rocket design, external forces such as air resistance, and the accuracy of input parameters. Generally, the more complex the model and the more accurate the input data, the more accurate the predictions will be.

3. Can these methods be used for modeling 3d rocket flight as well?

While these methods are specifically designed for 2d rocket flight, they can be extended to 3d by adding an additional dimension to the equations and variables. However, this may significantly increase the complexity and computation time of the model.

4. How do these methods handle uncertainties and variations in real-world scenarios?

These methods can take into account uncertainties and variations by using probabilistic methods and adding stochastic variables to the equations. This allows for a range of possible outcomes rather than a single precise prediction.

5. Are there any limitations or drawbacks to using these methods for modeling 2d rocket flight?

Some limitations of these methods include the assumption of a perfect and symmetrical rocket design, neglecting external forces such as wind and turbulence, and the need for accurate input parameters. Additionally, these methods may not accurately predict the behavior of the rocket during certain stages of flight, such as during separation events.

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