Propagation of uncertainty problem

In summary, the conversation was about finding the equivalent resistance and uncertainty for a circuit with multiple resistors. The solution involved using a formula for propagation of uncertainty, but the given answer was different from the calculated result. The expert suggests using absolute uncertainties instead of relative ones for simpler calculations.
  • #1
libelec
176
0

Homework Statement



Find the equivalent resistance viewed by A and B and its equivalent uncertainty:
http://img707.imageshack.us/img707/5040/dadadadaz.png

R1 = 10ohm, 5% tolerance.
R2 = 2ohm, 1% tolerance.
R3 = 5ohm, 5% tolerance.
R4 = 15ohm, 1% tolerance.

The Attempt at a Solution



The Req = (1/R1 + 1/R2)-1 + (1/R3 + 1/R4)-1 = 65/12ohm = 5,41ohm.

Now, for the uncertainty, I separated the problem in two: first, find RA (10/6ohm), the equivalent resistance of the first two resistors and RB (15/4ohm), the equivalent resistance of the second two resistors, and then add them.

I was given a formula for propagation of uncertainty for parallel resistors and for series resistors, based in the formula for a function f(x1, x2,..., xk): [tex]\mu[/tex]f = [tex]\sum[/tex]|(xk/f)*(f'xk)|*[tex]\mu[/tex]xk:

For two parallel resistors: [tex]\mu[/tex] = (R2/(R1+R2))*[tex]\mu[/tex]R1 + (R1/(R1+R2))*[tex]\mu[/tex]R2

For two series resistors: [tex]\mu[/tex] = (R1/(R1+R2))*[tex]\mu[/tex]R1 + (R2/(R1+R2))*[tex]\mu[/tex]R2

If I do the calculus, I get that the total uncertainty is 3,28%: the uncertainty of A is 2/(10+2)*0.05 + 10/(10+2)*0.01 = 1/60, and the one of B is 15/(15+5)*0.05 + 5/(15+5)*0.01 = 1/25. Then the total uncertainty is (10/6)/(65/12)*1/60 + (15/4)/(65/12)*1/25 = 0.0328 = 3.28%.

But the answer given by the problem says it has to be 8.7%.

I'd like to know if I'm using the formulas right, or if I should be doing something with the uncertainties instead of that.

Thanks.
 
Last edited by a moderator:
Physics news on Phys.org
  • #2
Anybody?
 
  • #3
I got the same result as you.

ehild
 
  • #4
Then the answer I was given is wrong? Or is there another method I could have used to reach that answer?

Thanks.
 
Last edited:
  • #5
Sometimes wrong answers are given. Your calculation was correct but a bit overcomplicated.

Unless the function is a product or fractions of its variables, calculate with absolute uncertainties instead of relative ones.

[tex]\Delta f = \Sigma (|\frac{\partial f }{\partial x_i}|\Delta x_i)[/tex]

Divide the absolute error with the value of f if relative uncertainty is needed.

ehild
 
Last edited:

FAQ: Propagation of uncertainty problem

What is the propagation of uncertainty problem?

The propagation of uncertainty problem is the challenge of estimating the uncertainty in the output of a mathematical model or measurement, given the uncertainties in the input variables. It is a fundamental issue in science, engineering, and statistics, as it affects the accuracy and reliability of any prediction or analysis.

How is uncertainty propagated in a mathematical model?

In a mathematical model, uncertainty is propagated through a series of mathematical operations, such as addition, subtraction, multiplication, and division. Each of these operations can introduce additional uncertainty in the output, which must be quantified and accounted for in the final result.

What methods are used to solve the propagation of uncertainty problem?

There are several methods used to solve the propagation of uncertainty problem, including Monte Carlo simulation, Taylor series expansion, and sensitivity analysis. Each method has its own advantages and limitations, and the choice of method depends on the type of model and the available data.

How does measurement error affect the propagation of uncertainty?

Measurement error is a major source of uncertainty in scientific measurements, and it can significantly impact the propagation of uncertainty. If the measurement error is known, it can be incorporated into the uncertainty analysis. However, if the measurement error is unknown, it can introduce additional uncertainty in the output.

What are the applications of the propagation of uncertainty problem?

The propagation of uncertainty problem has many applications in science and engineering, such as in weather forecasting, financial modeling, and risk assessment. It is also essential in experimental design, where uncertainty analysis is used to determine the number of replicates needed to achieve a desired level of precision.

Similar threads

Back
Top