Why Are Laplace Transforms Challenging in Differential Equations?

In summary, the person is seeking help with Laplace transforms and solving ODE's involving Heaviside and Dirac Delta functions. They are asking for assistance with two specific problems and are also looking for additional resources on these functions.
  • #1
cmmcnamara
122
1
Hi all, I'm taking a systems modeling class and as such a portion of the class consists of a differential equations review, mostly centered around Laplace transforms and some functions I've never had to deal with before so I was hoping for a bit of help if you'd all be so obliged! I have quite a few HW questions I can't seem to get just right.

The first one is to find the inverse laplace transform of:

[tex]f(s)=\frac{s+c}{(s+a)(s+b)^2}[/tex]

The way I went about this one was to separate one of the factors of [itex]\frac{1}{(s+b)}[/itex] out which itself has its own reverse transform in the table I'm using. Then I recognized the other factor as the polynomial quotient form which also has its own transform. Since I then had the product of two transforms, the total transform should be the convolution of the two inverses. My answer is very close to what Wolfram Alpha has to say is the proper inverse transform, but I am off by a factor:

[tex]F(t)=\frac{(a-c)(e^{-bt}-e^{-at})}{(a-b)^2}+\frac{c-b}{a-b}te^{-bt}[/tex]

I missing the factor of [itex]e^{-bt}[/itex] on the last term for some reason. I though I lost it during some portion of the convolution integral but I have triple checked my math and can't find anything.

Another problem I'm having is another missing factor in a problem finding the Laplace transform of a function:

[tex]F(t)=\mathcal{H}(t-5)(t-5)^4[/tex]

I recognized that the binomial can be expanded and then the Heaviside function distributed to each term. This sets up a series of transforms of the form [itex](-1)^nt^nF(t)[/itex] which has the transform of [itex]f^{(n)}(s)[/itex]. In this case f(s) is the transform of the Heaviside function. I get the following answer after differentiating and simplifying:

[tex]F(t)=\frac{-24e^{-5s}}{s^5}(26s^4-1)[/tex]

However Wolfram Alpha shows the proper answer is missing the factor of [itex]26s^4-1[/itex]. Can anyone verify this as being correct/incorrect?

Those are the only real issues I'm having dealing with Laplace transforms. The other issues I am having revolve around solving ODE's that use the Heaviside and Dirac Delta functions as forcing functions. I have never had to deal with these before and am having some interesting troubles solving equations involving these functions. Is there any elementary reading sources on these functions besides Wikipedia? I'm finding their explanation of these functions are a bit over my head in terms of basic understanding. I'm attempting to solve them at the moment with Laplace transform as asked in my HW assignments but unless the initial conditions are 0 such that those terms cancel out, I'm finding the reverse transforms to be exceedingly difficult due to the additive terms (from the initial conditions) causing convolutions using the mentioned functions (which is at least the only way as far as I can tell) and those integrals have me scratching my head. Any help would be appreciated, thank you!
 
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  • #2
What did you get when you separated the integrand into partial fractions?
 

Related to Why Are Laplace Transforms Challenging in Differential Equations?

1. What is systems modeling and why is it important?

Systems modeling is a process of creating simplified representations of complex systems in order to study and analyze their behavior. It is important because it allows scientists and engineers to better understand the relationships and interactions within a system, and to predict its behavior under different conditions.

2. What is the purpose of a systems modeling DE review?

A systems modeling DE review is conducted to evaluate the accuracy and effectiveness of a system model. It helps to identify any flaws or limitations in the model and to suggest improvements for better representation of the system.

3. How is a systems modeling DE review conducted?

A systems modeling DE review is typically conducted by a team of experts in the field who thoroughly examine the model and its underlying assumptions, data, and equations. They may also compare the model's predictions to real-world observations and perform sensitivity analysis to assess the model's robustness.

4. What are some common challenges in systems modeling DE review?

One common challenge in systems modeling DE review is the availability and quality of data. Models rely on accurate and reliable data to make accurate predictions, so any discrepancies or missing data can greatly impact the results. Another challenge is the complexity of the system being modeled, which may require simplifications and assumptions that could affect the model's accuracy.

5. How can systems modeling DE review benefit the scientific community?

Systems modeling DE review can benefit the scientific community by improving the accuracy and reliability of system models. This can lead to more informed decision-making in various fields, such as environmental management, public health, and engineering design. It also promotes transparency and collaboration among researchers, allowing for the advancement of knowledge in the field of systems modeling.

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