Simulation of the fission as a stochastic process

In summary, the conversation discusses a student's attempt to solve the Langevin equation numerically for the brownian motion. The student introduces new variables and equations to simplify the problem, but is struggling with the stochastic term. They are seeking help and guidance on how to proceed with their calculations.
  • #1
Heimdall
42
0
Hello


I'm a french student, I'm actually not sure this is the good place to ask my question but as it deals with the nuclear fission I try here... don't hesitate to tell me if there is a better forum... thx..


well, I'm trying to solve numerically the Langevin equation, initially for the brownian motion, it is also used in nuclear physics as you probably know, to describe the fission of nuclei...

the Langevin equation is :

[tex]\ddot{x}+\beta \dot{x} + \frac{1}{m}\frac{\partial U}{\partial x} = \Gamma(t)[/tex]

where [tex]\beta=\frac{\gamma}{m}[/tex] is a friction term (from a stocke's law) divided by the mass of the brownian particle. (so [tex]\beta[/tex] is [tex]s^{-1}[/tex])

[tex]U(x)[/tex] is an extern potential

and [tex]\Gamma(t)[/tex] is a stochastic force divided my the mass.


well, now I decide, as Kramers did, to tell that my potential U is represented by two parabolas as you can see on http://nicolas.aunai.free.fr/courb.htm


I call B the height of the maximum, and [tex]x_b[/tex] the correspondant X-coordonnate (assuming that the minimum will be at x=0)

I decide that B will be my caracteristic energy for the problem, and [tex]x_b[/tex] my caracteristc length.


I want, in order to solve my equation numerically, to write it without dimension, so I introduce the following new variables :

[tex]Q = \frac{x}{x_b}[/tex]

[tex]\Pi = \frac{U}{B}[/tex]

[tex]t'=\omega t[/tex] where [tex]\omega[/tex] is the caracteristic pulsation of my parabolas

i.e. the equations of the parabolas are :

[tex]U_1(x)=\frac{1}{2}m\omega^2 x^2[/tex] for [tex]x<x_0[/tex]

[tex]U_2(x)=-\frac{1}{2}m\omega^2(x-x_b)^2 + B[/tex] for [tex]x>x_0[/tex]

assuming the continuity of the potential, the functions and the derivatives shoud be equal between them at [tex]x_0[/tex] the junction point. these conditions give us the height B which is equals to :

[tex]\frac{1}{4}m\omega^2 x_b^2[/tex]


well now we have to re-write the langevin equation, replacing by the new variables... and here began my problems...


[tex]\ddot{x}+\beta \dot{x} + \frac{1}{m}\frac{\partial U}{\partial x} = \Gamma(t)[/tex]

[tex]\dot{x}[/tex] means [tex]\frac{dx}{dt}[/tex], so since we have [tex]t'=\omega t[/tex], the derivation by t' gives us an [tex]\omega[/tex]



[tex]\omega^2 x_b\ddot{Q}+\beta \omega x_b \dot{Q} + \frac{B}{m}\frac{\partial \Pi}{\partial Q} \frac{\partial Q}{\partial x} = \Gamma(t)[/tex]

we know that [tex]\frac{\partial Q}{\partial x} = \frac{1}{x_b}[/tex]

so we have :

[tex]\omega^2 x_b\ddot{Q}+\beta \omega x_b \dot{Q} + \frac{B}{mx_b}\frac{\partial \Pi}{\partial Q}= \Gamma(t)[/tex]


and with the B value we have :

[tex]\omega^2 x_b\ddot{Q}+\beta \omega x_b \dot{Q} + \frac{\omega^2 x_b}{4}\frac{\partial \Pi}{\partial Q}= \Gamma(t)[/tex]

finally, dividing by [tex]\omega^2 x_b[/tex] we obtain :

[tex]\ddot{Q}+\frac{\beta}{\omega}\dot{Q} + \frac{1}{4}\frac{\partial \Pi}{\partial Q}= \frac{1}{\omega^2 x_b}\Gamma(t)[/tex]

which I think is almost the result that I'm looking for.. since the first term is without dimention, [tex]\frac{\beta}{\omega}[/tex] is without dimension too, and the third term too..

my problem is the stochastic term...

now I don't know how to do with it... if you have an idea...

I now, that the autocorrelation function of the Langevin Force is :

[tex]<\Gamma(t)\Gamma(t')> = 2\beta T \delta(t_1-t_2)[/tex]

since [tex]t_i = \frac{t_i'}{\omega}[/tex], can I write the following equation :

[tex]<\Gamma(t)\Gamma(t')> = 2\beta T \delta(\frac{t_1'}{\omega}-\frac{t_2'}{\omega})[/tex]

and with [tex]\delta(a x)=\frac{1}{a}\delta(x)[/tex]

I find :

[tex]<\Gamma(t)\Gamma(t')> = 2\omega \beta T \delta(t_1'-t_2')[/tex]


so [tex]\Gamma(t)[/tex] should be proportionnal to [tex]\sqrt{(2\omega\beta T \delta(t_1'-t_2'))}[/tex]

in the nuclear system, k (the Boltzmann constant) is equal to 1, so we can also introduce the new variable :

[tex]\Theta=\frac{T}{B}[/tex]

so we can put it in our relation :

[tex]\Gamma(t)\ \ \ \alpha\ \ \ \sqrt{(2\omega\beta B\Theta\delta(t_1'-t_2'))}[/tex]


well... I'm not sure where I'm going with this... can someone help me ?


thanks !
 
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  • #2


Hello there, it's great to see that you are interested in nuclear physics and are trying to solve the Langevin equation numerically. This is definitely the right place to ask your question and I will do my best to help you out.

First of all, it is important to note that the Langevin equation is a stochastic equation, meaning that it involves random variables and cannot be solved deterministically. This is why you are having trouble with the stochastic term in your equation. The Langevin equation is typically solved using numerical methods, such as Monte Carlo simulations, to approximate the solution.

As for the rest of your calculations, they seem to be on the right track. However, I would suggest consulting with a nuclear physicist or a mathematician to ensure that your calculations are correct. Also, make sure to double check your units and ensure that they are consistent throughout your equations.

I hope this helps and good luck with your research! Don't hesitate to reach out if you have any further questions.
 
  • #3



Hello,

Thank you for your question and for sharing your work on simulating the fission process as a stochastic process. It seems like you have a good understanding of the Langevin equation and have made some progress in solving it numerically. However, I am not an expert in nuclear physics, so I cannot provide specific guidance on your equations. I would suggest seeking help from a professor or a more specialized forum for this topic.

One thing I can suggest is to check your units and make sure they are consistent throughout your equations. Also, it might be helpful to look at some existing literature on simulating fission as a stochastic process to see how others have approached it. This could give you some insight and potentially help you with your equations.

Overall, it seems like you are on the right track and have a good understanding of the concepts involved. Keep working on it and seeking help when needed, and I'm sure you will make progress. Good luck!
 

1. What is the purpose of simulating fission as a stochastic process?

The purpose of simulating fission as a stochastic process is to better understand the behavior and dynamics of nuclear reactions. By using mathematical models and computer simulations, scientists can study the probability and randomness of fission events, which can provide insights into the design and safety of nuclear energy systems.

2. How is the stochastic nature of fission taken into account in simulations?

In simulations of fission, the stochastic nature is taken into account by incorporating random variables and probability distributions into the mathematical models. This allows for the consideration of all possible outcomes and the likelihood of each outcome occurring, which is crucial for accurately representing the unpredictable nature of fission reactions.

3. What factors influence the stochastic behavior of fission?

The stochastic behavior of fission is influenced by several factors, including the type of nuclear material being used, the energy and intensity of the neutron source, and the physical conditions of the reaction environment. Other factors such as the presence of impurities or the shape of the nuclear fuel can also impact the stochastic nature of fission.

4. How do scientists use simulation data to improve nuclear energy systems?

Simulation data from fission as a stochastic process is used by scientists to analyze and optimize the design and operation of nuclear energy systems. By studying the probability and randomness of fission reactions, scientists can identify potential safety risks and make improvements to enhance the efficiency and reliability of nuclear energy production.

5. What are the challenges of simulating fission as a stochastic process?

Simulating fission as a stochastic process is a complex and computationally demanding task. One of the main challenges is accurately representing the randomness and probability of fission reactions, which requires advanced mathematical models and high-performance computing resources. Additionally, there may be uncertainties in the input parameters and limitations in the available data, which can affect the reliability of the simulation results.

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