Question on flow values in relationship with uncertainty

Hello, I would like to ask a question on what is the correct way to decide the flow values based on the raw data:
assuming that I got the value of goods A from the expert's estimation: the range of goods A is from 30 kg to 50 kg. The substance X containing in the goods A is: 5%-10% mass of goods A, also a range.
1) for goods A:
should I enter the flow value of goods A: 40 kg ± 10 kg (that would reach the minimum and the maximum of the range given by the expert.) OR should I calculate the standard deviation based on 30 and 50, that would be 14 kg and enter the values (40kg± 14 kg) in STAN?
2) for substance X:
based on the range of goods A and the range of substance X, I can build 4 extreme data samples for substance X: 30kg*5%; 30kg*10%; 50*5%; 50kg*10%. That would be 1.5; 3; 2.5; 5. So the mean value and standard deviation can be calculated based on these 4 values: 3kg ±1.5kg. Is this correct to enter 3kg ±1.5kg for substance X in STAN?
Another option would be to use TC (Transfer Coefficient) with uncertainty in STAN. Then, the similar question is raised as the question 1).

I would appreciate your insights!
thank a lot,
best,
Ran

Have a look at the following video (taken from our course Resource Management):
tube1.it.tuwien.ac.at/w/wNcmCZvjs2Vpdhrq5pitNk?start=29m35s

Between 29:35 and 31:58 I explain how I would do it. Apply the same approximation procedure to your mass flow values and the substance mass fractions and enter the results (mean value and standard deviation) as mass flow on the layer of goods and as mass fraction on the layer of the substance.

Thanks, Oliver, the calculation formula for the standard deviation in this case would be: S= (b-a) divided by √12 (the square root of 12). I am interested in where the "12" comes from. Is it from the GUM Annex F: F.2.2.2 Hysteresis or somewhere else in the GUM?
Thanks a lot!
best,
Ran

See en.wikipedia.org/wiki/Continuous_uniform_distribution . The standard deviation is the square root of the mentioned variance. Here, the derivation of the equation (taken from de.wikipedia.org/wiki/Stetige_Gleichverteilung , the German version of this Wikipedia page):