Abstract
This work presents an advanced reactor selection strategy that combines elements of a knowledge-based expert system to reduce the number of feasible reactor configurations with elaborated and automatised process simulations to identify reactor performance parameters. Special focus was given to identify optimal catalyst loadings and favourable conditions for each configuration to enable a fair comparison. The workflow was exemplarily illustrated for the Ru/C-catalysed hydrogenation of arabinose and galactose to the corresponding sugar alcohols. The simulations were performed by using pseudo-2D reactor models implemented in Aspen Custom Modeler® and automatised by using the MS-Excel interface and VBA. The minichannel packings, namely wall-coated minichannel reactor (MCWR), minichannel reactor packed with catalytic particles (MCPR), and minichannel reactor packed with a catalytic open-celled foam (MCFR), outperform the conventional and miniaturised trickle-bed reactors (TBR and MTBR) in terms of space-time yield and catalyst use. However, longer reactor lengths are required to achieve 99% conversion of the sugars in MCWR and MCPR. Considering further technical challenges such as liquid distribution, packing the reactor, as well as the robustness and manufacture of catalysts in a biorefinery environment, miniaturised trickle beds are the most favourable design for a production scenario of 5000 t/a galactitol. However, the minichannel configurations will be more advantageous for reaction systems involving consecutive and parallel reactions and highly exothermic systems.
Highlights
In industrial applications, almost every kind of holding or contacting equipment has been used as chemical reactors, e.g., mixing nozzles, centrifugal pumps, or the most elaborate tower or tube assemblies [1] (p. 549 ff)
From the extensive process simulations, a database was created that contains (a) the space-time yield with respect to the reactor volume or to the ruthenium mass, (b) the required reactor length, and (c) the specific energy consumption created by pressure drops at about 300 different flow conditions for each reactor configuration
This work presents an advanced reactor selection methodology that combines (a) elements of a knowledge-based expert system to reduce the number of feasible reactor designs to a reasonable number with (b) elaborated and automatised process simulations using pseudo-2D reactor models to identify reactor performance parameters at optimal operating conditions
Summary
Almost every kind of holding or contacting equipment has been used as chemical reactors, e.g., mixing nozzles, centrifugal pumps, or the most elaborate tower or tube assemblies [1] (p. 549 ff). Continuous processing with short downtimes dominates in the production of commodity/bulk chemicals, whereas batch processing typically encounters in the production of fine chemicals, specialties, and pharmaceuticals [2], and in the latter sectors, continuously operated and miniaturised reactors have emerged more frequently in the last decade often advertised as flow chemistry These mini- and microreactors offer increased yields and selectivities as well as require less space due to intensified heat and mass transfer and enable an operation within explosive regimes. In strategy level 1, the ideal size and shape of the catalyst, including its porous structure and distribution of active compounds, are specified These parameters affect the chemical reaction and the diffusive transport of reactants and products. By hByydhroygdernogateinoant,iothne, tmhiexmtuirxetucorentcaoinntianignignaglagcatloascetoasnedaanrdabairnaobsienomseaymbaeycboenvcoenrtveedrted intoingtaolagcatiltaoclti(tGoal l(OGHal)OaHn)daanrdabairtaobl i(tAorl a(AOrHa)O, Hw)h,iwchhricehprreespernetsevnatluvaabluleasbulegsaur gaalcroahlcoolsh,oalss, as discduisssceudssaebdovabeoavnedasnhdowshnowinnFiinguFriegu1r.e 1
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