(209c) Modeling and Simulation Challenges for Process Intensification

Modeling and Simulation
Challenges for Process Intensification

Efstratios
N. Pistikopoulos^1,2, David Sholl³, M. M. Faruque Hasan^1,2,
Salih E. Demirel^1,2 and Yuhe Tian^1,2, (1)Artie McFerrin
Department of Chemical Engineering, Texas A&M University, College Station,
TX, (2)Texas A&M Energy Institute, Texas A&M University, College
Station, TX, (3)School of Chemical & Biomolecular Engineering, Georgia
Institute of Technology, Atlanta, GA

The recently established Rapid
Advancement in Process Intensification Deployment (RAPID) Manufacturing
Institute aims to transform the U.S. industry by developing the next generation
of modular, intensified, and innovative manufacturing technologies and
processes. The RAPID Modeling and Simulation Focus Area will in particular address
the development of strategies and tools for the multi-scale representation,
modeling, optimization, and control of intensified systems. In this
presentation, we provide an overview of the challenges towards a systematic
synthesis, modeling, and simulation approach for process intensification, as
well as an exclusive review of process intensification synthesis approach methods
in the open literature, such as the ones included in [1-5]. We also introduce
an integrated framework for process intensification incorporating operability,
control and safety (illustrated in Figure 1).

Figure
1: An Integrated Framework for Process Intensification Incorporating
Operability, Control and Safety

[1] Demirel, S. E., Li, J., & Hasan, M.
F. (2017). Systematic process intensification using building blocks. Computers & Chemical
Engineering. http://doi.org/10.1016/j.compchemeng.2017.01.044.

[2] Baldea, M. (2015). From process integration
to process intensification. Computers
& Chemical Engineering, 81,
104-114.

[3] Tula, A. K., Babi, D. K., Bottlaender,
J., Eden, M. R., & Gani, R. (2017). A computer-aided software-tool for
sustainable process synthesis-intensification. Computers & Chemical
Engineering.  http://doi.org/10.1016/j.compchemeng.2017.01.001

[4] Papalexandri, K. P., &
Pistikopoulos, E. N. (1996). Generalized modular representation framework for
process synthesis. AIChE
Journal, 42(4),
1010-1032.

[5] Ismail, S. R.,
Proios, P., & Pistikopoulos, E. N. (2001). Modular synthesis framework for
combined separation/reaction systems. AIChE
Journal, 47(3),
629-649.