(500h) A Rapid Screening Methodology for Chemical Processes | AIChE

(500h) A Rapid Screening Methodology for Chemical Processes

Authors 

Frumkin, J. A. - Presenter, University of California, Santa Barbara
Doherty, M. F., University of California
Techno-economic analyses are an important part of evaluating potential chemical manufacturing ventures. A proposed conceptual process design gives the design engineer most of the information required to conduct these analyses; however, developing conceptual designs can be time consuming and expensive, and most conceptual designs never see commercialization. In this work, we present a rapid screening methodology to generate screening-level economic metrics (net present value and net present value percent1) without dedicating significant time or resources to conventional chemical process design. This methodology uses ultimate bounds on reaction selectivity combined with the minimum work of separations to bypass the design procedure altogether. The methodology presented here provides a means to rapidly screen chemistries for their economic merit, compare a proposed process design to the best-case economic scenario, and compare potential projects competing for the same funding sources. We present the necessary theory and demonstrate the methodology on the production of phthalic anhydride.

When conducting the techno-economic analysis of a proposed or hypothetical chemical process, the two sections of the process warranting the most consideration are the reaction section and the separations section. The reaction section of a chemical process has significant impacts on the economics as raw materials requirements are a large expense, typically accounting for up to 85% of total operating costs2. In a process with an inadequately designed reactor (and low reaction selectivity), a significant fraction of raw materials reacts to generate undesired byproducts and wastes instead of the desired product. The separations systems also greatly affect the process economics. Separations account for approximately 60% of energy requirements in chemical process, 95% of which (on an energy basis) is accomplished through distillation3. In addition to operating costs, the reaction and separations section contribute significantly to the capital cost of the chemical process.

Here, we present a methodology to determine estimates on economic metrics by using (1) the Continuous Flow Stirred Tank Reactor (CFSTR) Equivalence Principle4 combined with (2) the minimum work for separations. The CFSTR Equivalence Principle allows one to exactly represent any and every candidate reactor system for a chemistry using a single model (which we call a “Feinberg Decomposition”). We previously proved that the CFSTR Equivalence Principle can be used to determine ultimate bounds on reaction selectivity for a chemistry5, regardless if the chemistry is carried out at steady-state, batch-wise, or in a periodic or chaotic fashion6. Thus, the CFSTR Equivalence Principle can be used to model the reaction section in the screening-level analysis. The minimum work of separation required to separate the reactor effluents is easily calculated from flow rate and composition data, which are obtainable through material balance. This quantity, along with an appropriate multiplicative factor, is used to represent the separations section. Therefore, the only information required in this methodology are the kinetics for the chemistry of interest.

Using the methodology presented here, we can avoid both the detailed reactor design and the synthesis/conceptual design of a separations system. This in turn eliminates a significant amount of information that needs to be gathered, particularly for the separation system (e.g., information about phase equilibrium, presence of azeotropes, etc.) and allows for the rapid techno-economic analysis of potential chemical processes. The economic metrics we obtain are the net present value (NPV) and net present value percent (NPV%)1. These metrics take into account reaction and separation, but they do not correspond to a specified conceptual design. We therefore refer to these metrics as “screening level” metrics.

The screening methodology is demonstrated on the production of phthalic anhydride from o-xylene. We use this methodology to generate “best-case scenario” plots of NPV and NPV% as a function of overall process conversion. If these best-case economic metrics are not favorable, then the proposed chemistry can be abandoned as a possible business venture. We then compare the screening-level metrics of a conventional reactor design with the “best-case” economic metrics, allowing us to determine how much room for improvement exists. We find that there is a gap between the “best-case” screening-level metrics and the screening-level metrics of the conventional reactor, indicating that a more profitable process potentially exists. Additionally, the screening-level metrics of the Feinberg Decomposition reflect the trends we expect to see in a real process. In summary, the screening methodology presented here is a relatively easy-to-implement tool requiring very little information that can be of great assistance to design engineers.

References

  1. Mellichamp, D.A., 2013. New discounted cash flow method: Estimating plant profitability at the conceptual design level while compensating for business risk/uncertainty. Computers & Chemical Engineering 48, 251–263.
  2. Douglas, J.M., 1988. Conceptual Design of Chemical Processes. McGraw-Hill.
  3. Eldridge, R.B., Seibert, A.F., Robinson, S., Rogers, J., 2005. Hybrid separations/distillation technology. Research opportunities for energy and emissions reduction. Technical Report. University of Texas, Austin, TX (United States).
  4. Feinberg, M., Ellison, P., 2001. General kinetic bounds on productivity and selectivity in reactor-separator systems of arbitrary design: Principles. Industrial and Engineering Chemistry Research 40, 3181–3194.
  5. Frumkin, J.A., Doherty, M.F., 2018. Target bounds on reaction selectivity via Feinberg’s CFSTR Equivalence Principle. AIChE Journal. 64, 926–939.
  6. Frumkin, J.A., Doherty, M.F., "Ultimate bounds on reaction selectivity for batch reactors." Chemical Engineering Science. 199 (2019): 652-660.