One of my favorite activities as a chemical engineer is the development of new chemical/refining processes. A good portion of the upcoming blog postings will be associated with this activity. However, the computing needs for other activities, such as process trouble shooting, improvement, optimization, and control have much in common with the computing needs in process development. I hope the readers involved in those activities will continue to find these blogs interesting.
There are basically two ways to develop a new process...the "Scale Up" and "Scale Down" methods: I recommend the latter. Let's examine the two methods.
Scale Up
The steps in this method usually follow the sequence below:
- Catalyst screening and development using a small, laboratory reactor.
- Development of a conceptual process sequence.
- Scale up of the laboratory reactor to a pilot plant size with the addition of other process steps for study of recycle effects.
- Scale up of the pilot plant to commercial size.
Scale Down
The steps in this method follow:
- Catalyst screening and development as above.
- Development of a kinetic model using possibly another type of laboratory reactor, such as a Berty reactor.
- Development of a conceptual process design and simulation of the commercial scale process.
- Scale down of the commercial scale to the smallest possible pilot plant size.
- Determination or verification of design parameters using the pilot plant data.
- Final design of the commercial plant using the validated or updated parameters from the pilot plant program.
Dangers of the Scale Up Method
The first drawback to this method is that the pilot plant dimensions, primarily those of the reactor, may not be appropriate for the commercial process. By selecting the pilot plant dimensions without regard to the needs of the commercial unit (e.g. pressure drop or heat transfer), the scaling relationships, such as length/diameter are set at a non commercial value. When these dimensions are changed for the commercial design, it isn't a true scale up of the pilot plant.
An even greater error can be made when using the Scale Up method. Notice that the Scale Up method doesn't include the development of a kinetic model, nor does it include simulation of the commercial scale process. By skipping those steps, the wrong reactor type may be chosen for the process. Often, when the Scale Up method is followed, the reactor used to develop the catalyst (or reactions) is assumed to be the best reactor. However, a high heat exchange requirement, or a need to regenerate or resupply a catalyst may mean that another type of reactor would be a better choice. Without full simulation of the commercial process, these demands might be overlooked in the second step of the Scale Up sequence.
How does Scale Down differ?
In the Scale Down method, a simulation of the commercial design exists prior to the design of the pilot plant. That simulation involves many parameters. The pilot plant is then designed to improve the estimates of the most important, least well known parameters.
Two kinds of parameters are used to design processes...scale dependent and scale independent parameters. Examples of the latter are physical properties of fluids and their components, and properties of other materials, . The scale dependent parameters usually arise due to the use of a simplified model for a complex, often stochastic process. Examples of scale dependent parameters are axial and radial heat and mass dispersion coefficients, and gas fraction in a bubble column. The scale independent parameters are often well known. The uncertainty in the commercial design usually concerns the scale dependent parameters. (Note that scale dependent is not the same as extensive. A reaction rate constant is an extensive parameter that is not scale dependent.)
Correlations for the common scale dependent parameters have been developed and are found in the literature. Usually, these correlations are developed for a certain range of parameters such as Reynolds number, superficial velocity, ratio of catalyst diameter to reactor diameter. When scaling down the commercial reactor, these constraints for the correlations may limit the minimum size of the pilot plant reactor. In the Scale Up method, the pilot reactor may have been of a size that falls outside the correlations. Another advantage of the Scale Down approach is that some of the dimensional ratios can be kept constant for the commercial and pilot plant designs. For many correlations, the terms involving these ratios often will cancel, leaving a much simpler scaling relationship. By canceling these terms, some of the uncertainty in the correlation is removed.
Corporate Cultures
In my experience, the Scale Up method is the "default" method often used, even though I think most experienced engineers would agree that the Scale Down method is the better route. Organizational structure, the educational background of the management personnel and staff capabilities all can affect the choice of method. The corporate culture often plays a major role in the choice of method. Companies may temporarily use the Scale Down method, but as personnel change, the company lapses back into the default mode.
In future posts, I will examine some of the scale dependent parameters and how computing capabilities are changing the way we deal with these parameters. I could give examples of the two development methods and their outcomes, but enough is enough. If you have examples you wish to share, either successes or failures, please add your comments.
Next
I haven't picked my next topic, but I hope to work in some Mathcad in the next posting.
