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Process Modeling of Intensified Chemical Processes


Before the benefits of process intensification can be fully realized, a multitude of advances in process modeling will be necessary.

Process intensification (PI) has the potential to speed development of chemical engineering innovations. Among its many benefits, PI can increase the driving forces (physical and/or chemical) for transport phenomena, separations, and/or reactions in chemical processes, and it can inspire novel process configurations with major technical and economic benefits. Examples of PI applications include integrated process units such as heat exchange networks, sorption- or membrane-enhanced reactors, and dividing-wall distillation columns, among others (1).

Given the broad applicability of PI in both traditional and emerging chemical processes and given its focus on increasing energy efficiency in the chemical process industries (CPI), the RAPID Manufacturing Institute has targeted natural gas upgrading, chemical commodity processing, and renewable bioproducts as the initial focus areas for exploration of PI opportunities (1).

To realize the many benefits of PI, engineers will need to combine critical advances in process design principles, process modeling technology, and simulation tools. Process modeling technology captures the knowledge and insights for the experimental measurements, molecular science, and engineering fundamentals that ultimately facilitate reliable prediction of process performance.

There are four key domains required in the development of process modeling technology: data, thermodynamics, phenomena, and unit operations. Each domain forms the scientific foundation for the development of the following one.

For example, to develop process modeling technology for an intensified distillation process, engineers will need to work toward completing four steps (Figure 1). Each step is associated with one of the four domains:

  1. Data: compiling thermophysical properties and fluid-phase equilibrium measurements
  2. Thermodynamics: creating molecular thermodynamic models for multicomponent systems
  3. Phenomena: modeling fluid-phase equilibria phenomena
  4. Unit operations: developing multicomponent, multistage distillation unit operation models.


Figure 1. To develop process modeling technology for distillation processes, these four steps will be required. Each step corresponds to a domain of process modeling: data (navy blue), thermodynamics (green), phenomena (blue), and unit operations (gray).

The universal acceptance of existing process simulators for thermal separations has been built on numerous advances in multicomponent mixture measurements and molecular thermodynamic modeling of fluid-phase equilibria, as well as single-stage flash multistage distillation calculation algorithms (2). As we pursue PI opportunities in various chemical processes, traditional or emerging, critical advances in process modeling technology that capture the intensified process fundamentals are essential.

In fact, the RAPID Institute roadmap has clearly outlined many of the key challenges and opportunities in process modeling of intensified chemical processes. Among them are: fundamental data acquisition and/or analysis to generate databases to support process designs involving novel materials for reactions and separations; predictive models that capture intensified process fundamentals; and PI software tools that are widely accessible and capable of integrating PI solutions with existing unit operations (1).

This article explores some of the challenges and opportunities in modeling several high-impact, intensified chemical processes: biomass pyrolysis, gas adsorption, membrane separations, and electrochemical systems.


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