Discrepancy in the solution of a nonlinear dynamic system

In summary, the conversation discusses the use of the Energy Balance Method to solve a nonlinear dynamical system. The Hamiltonian is used to find an approximate analytical expression for the frequency of oscillation and the excitation force. However, there is a discrepancy between the obtained frequency and the nature of the system stiffness. The Hamiltonian is also discussed, with the article "APPLICATION OF THE ENERGY BALANCE METHOD FOR STRONGLY NONLINEAR OSCILLATORS" being referenced. The Hamiltonian is defined as the restatement of the energy balance of the system, with the inputted energy being equal to the sum of the potential energy and the kinetic energy. The usual definition of the Hamiltonian is also provided.
  • #1
dekarman
7
0
Hi,

I am solving the following nonlinear dynamical system using Energy Balance Method (EBM*). My intention is to arrive at an approximate analytical expression for the frequency of oscillation and the excitation force.

u''+u=A(1+2*u) with u(0)=u'(0)=0, where A is a constant (Physically it is like a Heaviside step loading).

I first write the Hamiltonian,

0.5*(u')^2+0.5*u^2=Au(1+2*u)

which implies the residue function R= 0.5*(u')^2+0.5*u^2-Au(1+2*u).

Then I assume the initial guess, which satisfies the initial conditions u=A*(1-cos(w*t)).

Then calculate R using the initial guess and collocate it at w*t=(pi/2) to obtain the relation between A and w.

However, the relation which I obtain is w=sqrt(1+4*A), which means that with increasing value of A, the frequency increases and hence indicates a hardening nature of the system stiffness.

However, by looking at the differential equation, this is clearly a softening system since the coefficient of u is (1-2*A).

I am not able to figure out this discrepancy.

Can somebody please point out where I am going wrong exactly.
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*Reference of EBM, APPLICATION OF THE ENERGY BALANCE METHOD
FOR STRONGLY NONLINEAR OSCILLATORS, H. Pashaei et al., Progress In Electromagnetics Research M, Vol. 2, 47–56, 2008, which is available on internet.

Thank you very much in advance.
Manish
 
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  • #2
I don't follow this at all. First, the Hamiltonian is not an equation so what you have written cannot possibly be the Hamiltonian. Second, what is your generalized momentum in this problem? And how did you go from your equations of motion to the Hamiltonian.
 
  • #3
Hi,

Thanks for your reply.

The Hamitonian H which I am writing is the restatement of the energybalance of the system. Since there is no damping, the inputted energy should be equal to the sum of the potential energy and the kinetic energy at any state of oscillation of the system. Subsequently,
H=KE+PE-inputted energy=0.
(You may please refer to the article to which I have referred to)

Now, H will be equal to zero if we use an exact solution of u. For any approximate solution, H is not equal to zero and there will be a residue R. I have collocated this at pi/2 since there is balance of PE and KE at that point.

I hope I have been able to throw a bit more light on the procedure.

Also, can you please tell the expression of the Hamiltonian which you are having in your mind?
------------------------------------------------------------------------------------------------

To get additional insight, consider the linear problem of spring mass system excited by a step force
u''+u=A

H function is 0.5*u'^2+0.5*u^2-Au=0, i.e. KE+PE-inputted energy=0
Take a guess of u as u=A*(1-cos(p*t)).

Substitute in H function, and collocate at any point between 0 to 2*pi, you will find that P=1.
Hence the exact solution is u=A*(1-cos(t)), which actually is the exact solution of the system.
 
  • #4
dekarman said:
The Hamitonian H which I am writing is the restatement of the energybalance of the system. Since there is no damping, the inputted energy should be equal to the sum of the potential energy and the kinetic energy at any state of oscillation of the system. Subsequently,
H=KE+PE-inputted energy=0.
The Hamiltonian is not, in general, equal to 0. Its time derivative is 0, which means that the Hamiltonian is constant.

dekarman said:
(You may please refer to the article to which I have referred to)
Could you provide a link?

dekarman said:
Also, can you please tell the expression of the Hamiltonian which you are having in your mind?
The usual definition of the Hamiltonian is:

[tex]\mathcal{H} = \sum_i p_i {\dot q_i} - \mathcal{L}[/tex]

Where L is the Lagrangian and the generalized momenta are given by:

[tex]p_i = \frac{\partial \mathcal{L}}{\partial {\dot q_i}}[/tex]
 

1. What causes discrepancies in the solution of a nonlinear dynamic system?

Discrepancies in the solution of a nonlinear dynamic system can be caused by a variety of factors, including modeling errors, numerical errors, and external disturbances. These discrepancies can also arise from the inherent complexity of nonlinear systems, which can lead to unpredictable and chaotic behavior.

2. How can discrepancies in the solution of a nonlinear dynamic system be minimized?

One way to minimize discrepancies in the solution of a nonlinear dynamic system is to improve the accuracy of the model used to describe the system. This can be achieved through careful calibration and validation of the model, as well as incorporating more sophisticated mathematical techniques and algorithms.

3. Can discrepancies in the solution of a nonlinear dynamic system be completely eliminated?

No, it is not possible to completely eliminate discrepancies in the solution of a nonlinear dynamic system. This is due to the inherent complexity and sensitivity of these systems, as well as the limitations of modeling and numerical techniques. However, these discrepancies can be minimized to a certain extent through careful analysis and improvement of the system model.

4. How do discrepancies in the solution of a nonlinear dynamic system affect the accuracy of predictions?

Discrepancies in the solution of a nonlinear dynamic system can significantly affect the accuracy of predictions, especially in the long term. This is because even small errors in the initial conditions or model parameters can lead to significant deviations in the system behavior over time. Therefore, it is important to carefully consider and account for these discrepancies when making predictions.

5. Can discrepancies in the solution of a nonlinear dynamic system be beneficial in any way?

Although discrepancies in the solution of a nonlinear dynamic system are generally viewed as undesirable, they can sometimes be beneficial. In certain cases, they can lead to new insights and discoveries about the behavior of the system, and can also help to identify weaknesses in the model or underlying assumptions. However, these benefits are often outweighed by the potential negative consequences of discrepancies in the system solution.

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