Resolving Plant Problems via Scaledown

Feb. 18, 2003

So you have a processing problem in your plant. What do you do?

One option is scaledown. The opposite of scaleup, scaledown involves the reduction in size of a large-scale process so the phenomena can be studied in the laboratory or in a pilot-plant facility. The scaled down version is more flexible and less expensive to operate than a plant.

By gaining process understanding from properly designed scaledown studies, plant personnel are better equipped to solve the problem.

But how do you go about scaledown? Very few "official" guidelines and rules of thumb exist. This column, however, provides some useful scaledown tips.

Define objectives

First, a strategy is needed for scaledown. You must establish the objectives of the scaledown. What is it you are trying to accomplish? If the objectives of scaledown are not established, then the scaledown will have no direction.

Often, the objective of scaledown is just a simple statement: The laboratory or pilot-plant facilities are to mimic plant conditions. This is actually a statement of process similarity. Whatever happens in the plant is similar to the phenomena in the laboratory or pilot-plant facility. In this way, plant phenomena can be studied more easily and inexpensively.

However, process similarity is vague and needs to be further quantified. Another question asks what chemistry and physics occur in the process. This information is needed. Unfortunately, you might not know the answer to this question. The answer then might become an additional objective of the scaledown.

Geometric similarity, often used in scaleup, might be helpful in scaledown, but is not required. The same physics and chemistry can occur in differing geometries. Modeling and flow visualization might be helpful in understanding the flow phenomena in plant operations.

Ask the right questions

Other questions need answering as well. What is the energy or power level the plant process receives? Power often can be thought of as the entity that accomplishes the process objectives (the process worker). Examples of inadequate workers might include insufficient pressure drop in fluid devices (pressure drop times flow rate equals power) or insufficient rotational speed to suspend solids in an agitated tank. Other types of workers exist as well. Process areas and lengths often are insufficient ," not enough heat transfer area is provided for heating or cooling or the trough level is too low for harvesting in flotation.

Where is the process actually taking place? This location can be thought of as the working volume in plant equipment. Most processes are not homogeneous, with different environments existing in the same process unit. The processing volume is what you want to scale down. Inventory volume can be neglected unless, of course, it appears to be the cause of the poor plant performance.

One principle in scaleup is to keep the ratio of the worker to the size of the job constant on scaleup. For plant operations, a condition is likely to exist in which the worker is not sufficient, providing the reason for poor plant performance. Energy/power level and working volume should be in roughly the same proportion between the plant and the scaledown studies.

Use educated guesses

In most cases, some data are not available or insight is insufficient to scale down precisely. In these cases, guessing might be in order. Keeping the same "appearances" helps. For example, poor mixing in a large tank in the plant could scale down to a vessel with no mixing in the laboratory. Here, time, length and velocity scales need to be kept similar between the plant and the laboratory.

In scaledown, do not be meticulous and fastidious. This is exploration, not true engineering or science. You are trying to attain some degree of similarity. Exact duplication of the plant in the laboratory is unlikely, as is exact identity with the plant.

Equations or equal signs for this type of work might not exist. Remember, you do not want to solve the plant problem in the laboratory ," you want to solve the plant problem in the plant. Avoid the famous statement: "We could do it in the lab. I don't know why they could not do it in the plant."

Tatterson is a technical editor for

Chemical Processing. He is a professor at North Carolina A&T State University in Greensboro. He also teaches short courses for the Center for Professional Advancement, Contact him at [email protected].