Non-ideal Flow Models Questions and Answers

Answer: C

Both reduce to the same behaviour when the spread is small, so the choice hardly matters there. They diverge for large deviations, where the physical picture behind each becomes important. Small deviations are model insensitive.

Answer: D

A closed vessel has plug flow at inlet and outlet while an open one has dispersion across the boundaries. The distinction affects how a measured variance is converted into a dispersion number. Closed vessels are the more common case.

Answer: A

The first two are correct. The third holds only in the limit of very small dispersion, where the boundary condition ceases to matter much, and for a vessel with appreciable back mixing the two cases give noticeably different dispersion numbers from the same measured variance.

Answer: B

The vessel is represented as active and dead volumes with some bypass, and each feature of the curve maps onto one element. It gives a physical picture that a one parameter model cannot. Each feature maps onto one element.

Answer: C

Building the model is a matter of adding just enough elements to reproduce the observed features. Adding more than the data justify makes the fit meaningless rather than better. Parsimony is the guiding principle here.

Answer: D

Both are true and the reason gives the discipline: a model with four parameters will fit almost any response, and the fit then says nothing about the vessel it was supposed to describe. Data must justify each parameter.

Answer: A

They correspond to the two extremes of micromixing and give the widest and narrowest conversion consistent with the distribution. The true value lies between them and the gap is often quite small. The two limits coincide for first order.

Answer: B

The first two are correct and describe the two limits. The third is wrong for first order, where the linearity makes the two limits coincide exactly. Micromixing matters only for other orders. The gap between the limits is often small.

Answer: C

Correct answer: the complete segregation model

Complete segregation is a *micromixing* model - it describes how fluid elements of different ages mix with one another, not how their residence times are spread. The other three are one-parameter descriptions of the spread itself: a dispersion coefficient, a number of tanks, or a fitted dead volume fraction.

Answer: D

Two models can reproduce the same distribution and still differ in their micromixing assumptions, which matters for non-linear kinetics. Fitting the flow is necessary but not sufficient. Kinetics decide whether the difference matters.