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Multiscale Analysis and Design for Process Intensi.. (MADPII)
Multiscale Analysis and Design for Process Intensification and Innovation
(MADPII)
Date du début: 1 mai 2012,
Date de fin: 30 avr. 2017
PROJET
TERMINÉ
"The current pressures on the major industrial players have necessitated a more urgent push for increased productivity, process efficiency, and waste reduction; i.e. process intensification. Future sizable improvements in these entrenched industrial processes will require either completely novel production technologies, fundamental analysis/modeling methods, or a combination of both. This proposal aims to approach this challenge by using multiscale modeling and experimentation on three fronts: (1) detailed analysis of industrial processes to generate new fundamental chemical understanding, (2) multiscale modeling and evaluation of high-volume chemical processes using a multiscale approach and fundamental chemical understanding, and (3) show the practical applicability of the multiscale approach and use it to critically examine novel technologies in the context of industrial processes. The novel technology portion of this proposal will be focused around a class known as rotating bed reactors in a static geometry (RBR-SG). We will investigate three processes that could benefit from RBR-SG technology: (1) fast pyrolysis of biomass, (2) gasification of biomass, and (3) short contact time catalytic partial oxidation of light hydrocarbons. Experimental reactor and kinetic work and validated computational fluid dynamics (CFD) modeling of the process mentioned above will be used. We will construct two RBR-SG units; heat transfer, adsorption, and pyrolysis gas/solid experiments will be performed in one, while non-reacting flow tests will be performed in the other with other phase combinations. Detailed kinetic models will provide novel insights into the reaction dynamics and impact other research and technologies. The combination of kinetic and CFD models will clearly demonstrate the benefits of a multiscale approach, will definitively identify the process(es) benefitting most from RBR-SG technology, and will enable a first design of the RBR-SG based on our results."
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