EPQ: Mathematical model of tea bag diffusion

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Discussion Overview

The discussion revolves around developing a mathematical model for the diffusion of tea from a tea bag into water, focusing on the concentration of tea over time. Participants explore various approaches to modeling this process, including ordinary differential equations (ODEs) and considerations of variables such as temperature and volume.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant expresses a desire to create a model for tea concentration as a function of time, seeking methods that allow for personal exploration rather than relying on established equations.
  • Another participant suggests using the ODE ##\frac{dC}{dt} = -kC## to model the concentration left in the bag, questioning whether the constant k should depend on other variables like temperature and volume.
  • Concerns are raised about the appropriateness of the ODE, as it models a decrease in concentration in the bag, while diffusion would lead to an increase in concentration in the water.
  • Participants discuss the implications of modeling the concentration of tea in the bag versus the concentration in the water, noting that both perspectives are valid.
  • One participant proposes a different ODE, ##\frac{dC}{dt} = -k(C-100)##, indicating that this could model the concentration reaching a maximum of 100% in the water.
  • There is a discussion about the complexity of the integrations involved and the level of mathematics required, with some participants suggesting that the math may exceed high school level.
  • Participants express uncertainty about incorporating additional variables such as temperature and volume into the model.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the best approach to modeling the diffusion process, with multiple competing views and methods being proposed. There is also uncertainty regarding the incorporation of additional variables.

Contextual Notes

Some discussions involve assumptions about the nature of the diffusion process and the mathematical techniques available, with participants acknowledging the limitations of their current knowledge and the complexity of the mathematics involved.

Who May Find This Useful

Readers interested in mathematical modeling, diffusion processes, or differential equations may find this discussion relevant.

Planckian
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I've done some research, and I've looked at the derivation of the diffusion equation, but I don't want to reproduce even a more simple version of it. I'd like something that can I do almost exclusively myself. The point of this is not to plot some graphs, and extract some line of best fit or exponential equation, but to work toward a model (tea concentration as a function of time, probably) that can fits data, with improvements being made accordingly. I've tried the Rayleigh method of dimensional analysis as a start, but with few variables, I couldn't see it though. So, are there any mathematical techniques/methods that you guys suggest I could use, or anything else? I'm not looking at something exact, but maybe an approximation for a cylinder, or sphere, maybe. Thanks so much.
 
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I would solve for concentration left in the bag C(t) by solving the ODE
##\frac{dC}{dt} = -kC## where k is a constant.
That is the simplest solution I can think of for the situation without the diffusion eq.
 
Shinaolord said:
I would solve for concentration left in the bag C(t) by solving the ODE
##\frac{dC}{dt} = -kC## where k is a constant.
That is the simplest solution I can think of for the situation without the diffusion eq.

I'm in high/secondary school, so I'm know expert in solving, but I know what it involves. Anyway, I had considered that, but would it not just give something of the form c(t)=c(0)*e^(-kt)? Or are you saying that k is a function of all of my other variables (temp, volume..)?
 
K would be based off of the data, say you had 60% of the tea left After 40 seconds. That would allow k to be found. With all of those variables, I don't think an OdE would be sufficient.
 
Shinaolord said:
K would be based off of the data, say you had 60% of the tea left After 40 seconds. That would allow k to be found. With all of those variables, I don't think an OdE would be sufficient.

Ah, I see, but having second thoughts, I don't thing it will work because it models a drop in concentration, whereas diffusing tea would result in conc increasing, and thereafter plateauing, right?
 
Well, the concentration of the tea left in the bag is decreasing as it dilutes with the water. It would have a minimum, when the water has the same concentration as the bag has left. If we were talking about the waters concentration, you would be correct. ( it would increase and plateau)
Either way is a valid model.
 
Shinaolord said:
Well, the concentration of the tea left in the bag is decreasing as it dilutes with the water. It would have a minimum, when the water has the same concentration as the bag has left. If we were talking about the waters concentration, you would be correct. ( it would increase and plateau

Yeah, I;m talking about the water's conc
 
Shinaolord said:
Well, the concentration of the tea left in the bag is decreasing as it dilutes with the water. It would have a minimum, when the water has the same concentration as the bag has left. If we were talking about the waters concentration, you would be correct. ( it would increase and plateau)
Either way is a valid model.

I've been sitting here all day, not really sure where to go (well, I have a few ideas), but are you sure there isn't anything else you know of? It doesn't have to be simple
 
If I knew pde'a possibly. I'm trying to find a good diff eq to model it.
Edited for spelling.
 
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  • #10
Shinaolord said:
If I knew pde'a possibly. I'm trying to find a gold diff eq to model it.

Not sure what that means, but, ok
 
  • #11
Something such as ##\frac{dC}{dt} = -k(C-100)## where I chose 100 because I wanted it to max at 100%.
Graph the solution of that. Does that look like you would expect? I can graph it for you if you can't.

pDE are partial differential equations, like the diffusion equation with ##\partial## derivatives. It's higher level math.

Edited for correct signs.
My previous post should've said good model not gold lol.
 
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  • #12
Shinaolord said:
Something such as ##\frac{dC}{dt} = -k(y-100)## where I chose 100 because I wanted it to max at 100%.
Graph the solution of that. Does that look like you would expect? I can graph it for you if you can't.

pDE are partial differential equations, like the diffusion equation with ##\partial## derivatives. It's higher level math.

Edited for correct signs.
My previous post should've said good model not gold lol.

Thanks, will look at it. What is y? Just a constant?
 
  • #13
Well y is the concentration of tea in the water. You can use c' and c if that makes it clearer for you.

Edit my bad. I see what you meant. I fixed my previous post.
 
  • #14
Shinaolord said:
Well y is the concentration of tea in the water. You can use c' and c if that makes it clearer for you.

Edit my bad. I see what you meant. I fixed my previous post.

If I integrate, I get c(t)=kt(100-y). I already have a c term. So is y the same thing? Thanks
 
  • #15
So you know, the solution is ##C =p*e^{-kt}+100 ## where p is a constant, and e the natural base =2.7... . Since at t=0 there is no tea in the water, we have p*e^0t+100=0 which is the same as p+100=0. So p=-100.
 
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  • #16
Planckian said:
If I integrate, I get c(t)=kt(100-y). I already have a c term. So is y the same thing? Thanks
These integrations are more complex than that. Have you heard of wolfram alpha? It should give a step by step solution so you can see. P.s. At high school leve, this math is totally unnecessary. It's 2nd/3rd year college lvl.
 
  • #17
Shinaolord said:
These integrations are more complex than that. Have you heard of wolfram alpha? It should give a step by step solution so you can see. P.s. At high school leve, this math is totally unnecessary. It's 2nd/3rd year college lvl.

For this project, I have to go beyond what I know
 
  • #18
Ok. Well the graph should look like this; is it what you expect?
ImageUploadedByPhysics Forums1407606257.679452.jpg
 
  • #19
Shinaolord said:
Ok. Well the graph should look like this; is it what you expect?
View attachment 72031

Wow. Thanks
 
  • #20
Your welcome. I hope that was what you're looking for! :)
 
  • #21
Planckian said:
Wow. Thanks

Do you think there's an good way of incorporating variables like temp and volume of water?
 
  • #22
Not that I know of. You could wait until someone more knowledgeable replies though. I'm not sure if it's possible.
 
  • #23
Shinaolord said:
Not that I know of. You could wait until someone more knowledgeable replies though. I'm not sure if it's possible.

Thanks so much. This was very nearly going to be a wasted day(!)
 
  • #24
Your welcome. Differential equations are fascinating, they make math wonderous in my opinion.
 
  • #25
Shinaolord said:
Your welcome. Differential equations are fascinating, they make math wonderous in my opinion.

Agreed
 

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