Home | DTI | 2011–12 funded proposals | Prodromos Daoutidis, Eric Van Wyk, Aditya Bhan
Prodromos Daoutidis, Eric Van Wyk, Aditya Bhan
Extensible language-oriented computational framework for process engineering of biorefineries
Biorefineries are envisaged to produce "green" transportation fuels and chemicals by upgrading biomass in a sequence of steps, akin to a petroleum refinery. Engineering different processes of a biorefinery entails computational tasks at various levels, spanning several time and length scales: elucidation of the underlying chemistry at the mechanistic level, modeling and design at the reactor and process level, and an enterprise level analysis of process economics and environmental considerations.
Solutions spanning multiple levels of computations allow for rigorous and comprehensive analysis of process alternatives. However, this necessitates a unifying and overarching software infrastructure that allows for integration of computational packages, numerical libraries, independent and custom-built programs in a seamless manner to provide solutions to specific process engineering problems. The major long term goals of this work are two-fold. First, we propose to develop a software engineering infrastructure in the form of an extensible language framework for process engineering. This framework will build on a general purpose language such as C++, by incorporating domain-specific syntax and semantics spanning over the four levels of process engineering. Multifunctional thermochemical conversion of lignocellulose to transportation fuels and chemicals has been shown to be very promising for ugrading biomass. Process engineering solutions encompassing all four levels are critical towards the implementation of this technology.
The second goal of this work is to: (a) elucidate the underlying mechanisms of multifunctional thermochemical conversion systems, (b) develop reactor models with detailed chemistry and accurate kinetics, (c) evaluate process designs of multiple thermochemical conversion schemes with novel separation strategies, and (d) solve enterprise-level issues such as plant location, sizing, and economics.
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