(6if) An Open Source Process Simulation Environment on Python for Automated Preliminary Techno-Economic Analysis | AIChE

(6if) An Open Source Process Simulation Environment on Python for Automated Preliminary Techno-Economic Analysis

Authors 

Kummar, D., University of Illinois at Urbana-Champaign
Singh, V., University of Illinois at Urbana-Champaign
Guest, J., University of Illinois at Urbana-Champaign
Research Interests:

Software development of process simulation components and platforms. Biofuel and bioproduct production. Technological development pathways based on quantitative sustainable design.

Teaching Interests:

Any undergraduate chemical engineering course and senior design. Biofuel and bioproduct production. Working with CAPE-OPEN platforms.

Abstract:

A fast and flexible open source simulation environment on python is being developed for automated preliminary technoeconomic analysis. The development and evaluation of a production process is a complex task that involves minimizing both cost and environmental impact while satisfying design specifications and product requirements. Therefore, tailoring a design to study how different feed compositions and design parameters impact its sustainability is a laborious task. To automate this task, the simulation environment allows for easy implementation of simplifying assumptions that lie within marginal error in the final cost evaluation. Additionally, an efficient recycle converging algorithm is employed whereby mass balances are solved without the need for any rigorous calculation. After each outer iteration of a rigorous simulation loop, an inner loop based on mass balances and collected simulation data is converged. The simulation environment maintains accuracy in rigorous thermodynamic calculations with the aid of standard CAPE-OPEN thermodynamic packages and the Chemical Engineering Design Library on python. The validity of the simulation environment to correctly predict production costs will be tested by reevaluating a design for the co-production of ethanol and biodiesel from lipid cane. The automation capabilities will be tested by varying design parameters in a Monte Carlo framework and performing multivariable sensitivity analysis. The overarching goal of the python simulation environment is to better prioritize research and development by evaluating how possible technological innovations can impact the sustainability of a production process. This open source simulation environment would allow third party designs and unit operations to be easily shared without any economic barriers. Researchers would benefit with the capability to test the implications of their technological innovations.