A simple simulation for chemical-looping combustion (CLC) is discussed: two, coupled fluidised reactors with steady circulation of particles of oxygen carrier between them. In particular, the sensitivity of CLC to different particle kinetics is investigated. The results show that the system is relatively insensitive to different kinetics when the mean residence time of particles in each reactor is greater than the time taken for them to react completely.This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S0009250916302779

Dennis, JS

Schnellmann, MA

Scott, SA

Williams, G

Apollo (Cambridge)

Chemical Engineering Science 152 (2016) 21–25Contents lists available at ScienceDirectChemical Engineering Sciencehttp://d0009-25n CorrE-mjournal homepage: www.elsevier.com/locate/cesShort CommunicationSensitivity of chemical-looping combustion to particle reaction kineticsM.A. Schnellmann a,n, S.A. Scott b, G. Williams c, J.S. Dennis aa University of Cambridge, Department of Chemical Engineering and Biotechnology, Pembroke Street, Cambridge CB2 3RA, UKb University of Cambridge, Department of Engineering, Trumpington Street, Cambridge CB2 1PZ, UKc Johnson Matthey Technology Centre, Blounts Court Road, Sonning Common, Reading RG4 9NH, UKH I G H L I G H T S In a reactor-regenerator system, if particles have mean residence times in each reactor greater than the time taken for them to react completely, it isinsensitive to kinetics. There is scope for approximating detailed particle kinetics using simple models. For chemical-looping combustion, a shrinking core model under product layer diffusion control is a suitable approximation for the behaviour of oxygencarrier particles.a r t i c l e i n f oArticle history:Received 12 October 2015Received in revised form11 March 2016Accepted 21 May 2016Available online 21 May 2016Keywords:Chemical looping combustionFluidizationKineticsOxygen carrierRedoxSimulationx.doi.org/10.1016/j.ces.2016.05.02809/& 2016 The Authors. Published by Elsevieesponding author.ail address: mas227@cam.ac.uk (M.A. Schnellma b s t r a c tA simple simulation for chemical-looping combustion (CLC) is discussed: two, coupled ﬂuidised reactorswith steady circulation of particles of oxygen carrier between them. In particular, the sensitivity of CLC todifferent particle kinetics is investigated. The results show that the system is relatively insensitive todifferent kinetics when the mean residence time of particles in each reactor is greater than the timetaken for them to react completely.& 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license(http://creativecommons.org/licenses/by/4.0/).1. IntroductionChemical-looping combustion (CLC) offers the possibility ofburning fossil fuels whilst separating the CO2 produced. The pro-cess involves the redox cycling of an oxygen carrier, typically atransition metal oxide, e.g. the combustion of methane:+ → + + ( )4MeO CH 4Me 2H O CO 14 2 2+ → ( )4Me 2O 4MeO 22+ → + ( )CH 2O 2H O CO 34 2 2 2The oxygen carriers are contacted with the fuel in their oxi-dised form so that the lattice oxygen in the solid reacts via reaction(1). The gaseous product, after removal of water, is a stream ofr Ltd. This is an open access articlann).pure CO2 suitable for sequestration. The reduced carrier is re-oxidised with air (reaction (2)). Complete conversion from MeO toMe and back to MeO will not necessarily be obtained in a realsystem. Overall, the hydrocarbon has been burnt in air (reaction(3)), so the total enthalpy change is the same as for conventionalcombustion (Lyngfelt et al., 2001).An option for CLC is to use two interconnected ﬂuidised re-actors, as shown in Fig. 1. Here, the two sub-reactions are sepa-rated spatially, with reduction of the oxygen carrier in the fuelreactor and oxidation in the air reactor. Most pilot-scale CLC sys-tems use variants of this basic conﬁguration (Adanez et al., 2012).There has been signiﬁcant research on measuring the redoxkinetics of carriers at the laboratory scale (Adanez et al., 2012), butalmost nothing published on the important question of howknowing the kinetics of an individual particle would affect thedesign of the system in Fig. 1. Indeed, in some cases, e.g. experi-ments to determine the rate of oxidation at high temperature, it isalmost impossible, experimentally, to determine the intrinsic ki-netics because they are so fast that experiments are confounded bye under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Fig. 1. Schematic of CLC concept.M.A. Schnellmann et al. / Chemical Engineering Science 152 (2016) 21–2522various mass and heat transfer effects. Here, we investigate thesensitivity of reactor behaviour to the kinetics of individualparticles.Table 1Properties of the oxygen carrier particle for the detailed particle model (Chuanget al., 2009).Property ValueDiameter 300 mmSkeletal density 4500 kg/m3Porosity 0.75Tortuosity 3BET surface area 4.5107 m2/m3Mean pore radius 37 nmIntrinsic ﬁrst order rate constant(reduction)6.5107exp(52 kJ/mol/RT) s1Intrinsic ﬁrst order rate constant (oxidation) 8.2106exp(44 kJ/mol/RT) s1Diffusion boundary layer thickness(reduction)1196 mmDiffusion boundary layer thickness(oxidation)1263 mm2. Model development2.1. Cycling behaviourThe simple situation in Fig. 1 was considered: two, coupledﬂuidised bed reactors, well-mixed with respect to solids, withsteady circulation between them. In terms of gas-solid contact, it isassumed that the time for a particle to sample the whole bed ismuch less than the residence time of a particle in the bed. As aresult a particle will sample the complete gas proﬁle of the bedmany times. An average gas concentration can therefore be used.No reaction or mixing was assumed to occur in the connectinglines and all particles were assumed to have identical physical andchemical properties, other than state of conversion. Since the re-actors are well-mixed with respect to solids, and assuming noelutriation, the residence time distribution (RTD) function for theparticles for both reactors is:( ) = ̅ ( )− ̅E tte14ttwhere ̅t is the mean residence time of particles in the reactor andt is the time a particle spends in the reactor.Monte Carlo (MC) simulation was used to determine the meanconversion and rate of reaction of particles as they leave the re-actors. The simulation was begun with a fully-oxidised particle fedto the fuel reactor. The particle leaves having spent time in thereactor chosen by inverse transform sampling (ITS) from the RTDfunction:=− ̅ ( ) ( )t t Uln 5where U is a random number between 0 and 1. Once the particlehas spent this time in the fuel reactor, it was fed to the air reactor.Similarly, the time spent in the air reactor was determined by ITS.When the particle exited the air reactor, the ﬁrst cycle was com-plete. The process was repeated for 1000 cycles. The methodologyis similar to that used by Kimura et al. (1979). Tracking the localstate of conversion of particles is important, since particles canbuild up complex local distributions of reactant and product asthey are cycled between the two reactors. Chuang et al. showedexperimentally that sharp transitions between reactant and pro-duct can be present after both oxidation and reduction reactions(Chuang et al., 2010, 2009). In the present work, the simulationwas performed for shrinking core models (SCMs) (chemical reac-tion, product layer diffusion and external gas ﬁlm control), uni-form reaction, and for a detailed model of a single particle,described in Section 2.2.2.2. Detailed model of a single particleHere, the expressions for intrinsic kinetics were coupled withthe Stefan-Maxwell equations. Allowance was made for externalmass transfer by applying the Stefan-Maxwell equations to thetransport of gases over a deﬁned ﬁlm thickness of particulatephase (Saucedo et al., 2014). The thickness of the diffusionboundary layer was calculated as described by Hayhurst (2000)and Dai et al. (2016). To account for temperature gradients, anappropriate form of the energy equation was used (see Supple-mentary Information). The particle was assumed to be sphericalwith a homogeneous structure of monosized pores, which wereunaffected in size by the reaction.3. ResultsThe detailed particle model was used to model the reduction(reaction (6)) and oxidation (reaction (7)) of a single particle ofoxygen carrier containing CuO and Al2O3 (82.5 wt% CuO) at 850 °C,with properties given in Table 1. The reducing environment was,on a molar basis, 5% CO in 2.5% CO2 and 92.5% N2, while the oxi-dation was with 5% O2 in N2. For oxidation in air at 850 °C, theequilibrium lies towards CuO rather than Cu2O (Gayán et al., 2012).+ → + ( )CuO CO Cu CO 62+ → ( )2Cu O 2CuO 72The predicted behaviour of a particle over two redox cycles isshown in Fig. 2, for the case of the particle having insufﬁcient timeto react completely. Even after two cycles, the particle has acomplicated distribution of reactant and product, conﬁrming thatthe modelling approach, described in Section 2.1 is essential.Using the detailed and simple models, a single particle ofoxygen carrier was cycled 1000 times between the reactors fordifferent values of θ , given by:θ =̅ ( )tt 8totwhere ttot is the time taken for a fresh particle to react completelyin a reactor, and ̅t is its mean residence time in that reactor: ttot isnot necessarily the same for different kinetics. The smaller θ is, thelonger the particle spends in the reactors. Since every particlecarries the complete statistics of the process, which remain con-stant throughout the simulation, the ergodic hypothesis can beinvoked. This says that cycling a particle 1000 times is equivalent00.20.40.60.810 0.2 0.4 0.6 0.8 1Conversion (0 -oxidised, 1 -reduced)Non-dimensional particle radius (0 -centre, 1 - surface)00.20.40.60.810 0.2 0.4 0.6 0.8 1Conversion (0 -oxidised, 1 -reduced)Non-dimensional particle radius (0 -centre, 1 - surface)00.20.40.60.810 0.2 0.4 0.6 0.8 1Conversion (0 -oxidised, 1 -reduced)Non-dimensional particle radius (0 -centre, 1 - surface)00.20.40.60.810 0.2 0.4 0.6 0.8 1Conversion (0 -oxidised, 1 -reduced)Non-dimensional particle radius (0 -centre, 1 - surface)Fig. 2. Evolution of particle conversion with cycling. The particle is initially fully oxidised, it exits the fuel reactor after 20 s (a), then spends 6 s in the air reactor (b), followedby 8 s in the fuel reactor (c) and ﬁnally 1 s in the air reactor (d). The times have been chosen to illustrate the importance of conversion history.00.20.40.60.810.01 0.1 1 10Conversion (0 -oxidised, 1 -reduced)θSCM Chemical reaction control (analytical)SCM Chemical reaction controlSCM Product layer diffusion controlSCM External gas film controlUniform reactionFuel reactorAir reactorFig. 3. Mean particle conversion for simple models.M.A. Schnellmann et al. / Chemical Engineering Science 152 (2016) 21–25 23to cycling 1000 particles once. This MC method therefore providesa useful insight into the behaviour of particles during cycling. Allthe results shown are for identical θ in both reactors.The relationship between the conversion of the particle, whenit leaves a reactor, and the mean residence time in the reactors isshown for different simple models in Fig. 3. Since the reactors arewell-mixed with respect to solids, the mean conversion whenleaving the reactor is equivalent to the mean conversion withinthe reactor. The analytical solution (Kimura et al., 1979) for a SCMunder chemical reaction control is also shown. Fig. 3 shows thatfor mean conversion, the agreement between the simple models isgood for θ < 1, except for a SCM under external gas ﬁlm control,where agreement is good for θ < 0.1.In Fig. 4, the result for the detailed particle model is comparedto that for a SCM under product layer diffusion control. Overallthere is excellent agreement, with only slight deviations at high θ .Fig. 5 shows how the mean rate of reaction of a particle fordifferent simple models varies with mean particle residence time.The analytical solution for a SCM under chemical reaction controlis also shown. As for conversion, the mean rate when leaving thereactor is equivalent to the mean rate in the reactor. The rate hasbeen normalised with respect to the analytical value for a SCMunder chemical reaction control when θ=1, thus the results forreduction and oxidation are the same. Agreement between the00.20.40.60.810.01 0.1 1 10Conversion (0 -oxidised, 1 -reduced)θSCM Chemical reaction control (analytical)SCM Product layer diffusion controlDetailed particle modelAir reactorFuel reactorFig. 4. Mean particle conversion for the detailed particle model to a SCM underproduct layer diffusion control.012345670.01 0.1 1 10Normalised rate of reactionθSCM Chemical reaction control (analytical)SCM Chemical reaction controlSCM Product layer diffusion controlSCM External gas film controlUniform reactionFig. 5. Mean particle reaction rate for simple models.01234560.01 0.1 1 10Normalised rate of reactionθSCM Chemical reaction control (analytical)SCM Product layer diffusion controlDetailed particle model (air reactor)Detailed particle model (fuel reactor)Fig. 6. Mean particle reaction rate for the detailed particle model and a SCM underproduct layer diffusion control.M.A. Schnellmann et al. / Chemical Engineering Science 152 (2016) 21–2524simple models is good for θ<0.5.Finally, Fig. 6 compares the results for the detailed particlemodel with a SCM under product layer diffusion control; there isexcellent agreement for θ<5.The results shown in this section did not depend on the initialconversion of the particle. For θ< <0.01 10, simulations with dif-ferent initial conversions gave identical results. Initial conversionis only important for θ > 50.4. DiscussionIn CLC, particles will not necessarily react to completion as theyare cycled between the two reactors; accordingly, their reactionhistory is important. Since there is a RTD for the particles, even ifthe mean residence time is greater than the time for completereaction (θo1), they will nevertheless regularly spend less time inthe reactor than is needed for them to react completely. Fig. 2illustrates how; over time, a particle can build up concentric shellsof reactant and product, as postulated also by Kimura et al. (1979)for cracking catalyst.The results for simple particle reaction models (SCMs anduniform reaction) are similar provided that θ<1 for conversion andθ<0.5 for rate of reaction, as shown in Figs. 3 and 5. The exceptionis for a SCM under external gas ﬁlm control, where conversionresults are similar when θ<0.1. CLC is likely to be operated be-tween θ< <0.2 1 to achieve an optimal balance between a lowcirculation rate and a low inventory of oxygen carrier. The ﬁndingsdescribed in this paper are therefore important, because theyshow that CLC is relatively insensitive to different particle kinetics.This is expected because, as θ gets smaller, the particles react tocompletion more frequently. As a fraction of their residence time,they therefore spend less time in the range of conversion (0.1–0.9),where different kinetics diverge the most.CLC is one example of a reactor-regenerator system. The ob-servation that when θ<1, CLC is insensitive to different particlekinetics, is therefore relevant for other processes, e.g. ﬂuidisedcatalytic cracking, systems for the removal of H2S and other gasesfrom gasiﬁcation or combustion, chemical-looping reforming andcalcium-looping. There is also scope for approximating detailedparticle models using simple ones. This observation is very usefulwhen θ>1, since a simple particle model decreases signiﬁcantlythe computational time required for an overall process model tosolve. It is also beneﬁcial for cases where the intrinsic kinetics aredifﬁcult to obtain experimentally e.g. oxidation at high tempera-tures. For the CLC process, described in this paper when θ < 5,there is excellent agreement between the detailed model and aSCM under product layer diffusion control. The small deviationwhen θ > 5, is because the rate of external mass transfer begins tohave a limiting effect.5. ConclusionsA simple simulation of CLC has been developed, which showedthat the process was relatively insensitive to different particle ki-netics, when the mean residence time of the particles was greaterthan the time taken for them to react completely ( θ<1). This isimportant because CLC is likely to be operated with low θ . Inaddition, this result is relevant for other reactor-regenerator sys-tems. It was also shown that a SCM under product layer diffusioncontrol was an excellent approximation for the detailed particlemodel when θ < 5, demonstrating scope for using simple modelsin simulations of CLC systems.AcknowledgementsThe authors are grateful for ﬁnancial support from the En-gineering and Physical Sciences Research Council and JohnsonMatthey plc. through an Industrial CASE Studentship.ReferencesAdanez, J., Abad, A., Garcia-Labiano, F., Gayan, P., de Diego, L.F., 2012. Progress inchemical-looping combustion and reforming technologies. Prog. En-ergy Combust. Sci. 38 (2), 215–282. http://dx.doi.org/10.1016/j.pecs.2011.09.001.Chuang, S.Y., Dennis, J.S., Hayhurst, A.N., Scott, S.A., 2009. Kinetics of the chemicallooping oxidation of CO by a co-precipitated mixture of CuO and Al2O3. Proc.Combust. Inst. 32 (2), 2633–2640. http://dx.doi.org/10.1016/j.proci.2008.06.112.Chuang, S.Y., Dennis, J.S., Hayhurst, A.N., Scott, S.A., 2010. Kinetics of the oxidationof a co-precipitated mixture of CU and Al 2O3 by O2 for chemical-loopingcombustion. Energy Fuels 24 (4), 3917–3927. http://dx.doi.org/10.1021/ef1002167.Dai, P., Dennis, J.S., Scott, S.A., 2016. Using an experimentally-determined model ofM.A. Schnellmann et al. / Chemical Engineering Science 152 (2016) 21–25 25the evolution of pore structure for the gasiﬁcation of chars by CO2. Fuel 171,29–43. http://dx.doi.org/10.1016/j.fuel.2015.12.041.Gayán, P., Adánez-Rubio, I., Abad, A., de Diego, L.F., García-Labiano, F., Adánez, J.,2012. Development of Cu-based oxygen carriers for Chemical-Looping withOxygen Uncoupling (CLOU) process. Fuel 96, 226–238. http://dx.doi.org/10.1016/j.fuel.2012.01.021.Hayhurst, A.N., 2000. The mass transfer coefﬁcient for oxygen reacting with acarbon particle in a ﬂuidized or packed bed. Combust. Flame 121 (4), 679–688.http://dx.doi.org/10.1016/S0010-2180(99)00178-9.Kimura, S., Fitzgerald, J., Levenspiel, O., Kottman, C., 1979. Solid circulation systemswith shrinking core kinetics in both reactor and regenerator. Chem. Eng. Sci. 34,1195–1201.Lyngfelt, A., Leckner, B., Mattisson, T., 2001. A ﬂuidized-bed combustion processwith inherent CO2 separation; application of chemical-looping combustion.Chem. Eng. Sci. 56, 3101–3113.Saucedo, M.A., Lim, J.Y., Dennis, J.S., Scott, S.A., 2014. CO2-gasiﬁcation of a lignitecoal in the presence of an iron-based oxygen carrier for chemical-loopingcombustion. Fuel 127, 186–201. http://dx.doi.org/10.1016/j.fuel.2013.07.045.

Sensitivity of chemical-looping combustion to particle reaction kinetics

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