Solid Catalyst Alkylation of C2âC3 Olefins with Isobutane in the

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Solid catalyst alkylation of C2-C3 olefins with isobutane in presence of hydrogen using a slurry transport reactor-hydrocycloneregenerator system and PtSO4TiZr/SiO2 catalyst. II. Regeneration of spent catalysts in pilot plant and simulation of a FBR. Roberto E. Galiasso Tailleur, Carlos Farina, Sergio Rodriguez, and Sylvana Derjani-Bayeh Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b03477 • Publication Date (Web): 01 Jan 2018 Downloaded from http://pubs.acs.org on January 2, 2018

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Solid catalyst alkylation of C2-C3 olefins with isobutane in presence of hydrogen using a slurry transport reactor-hydrocycloneregenerator system and PtSO4TiZr/SiO2 catalyst. II. Regeneration of spent catalysts in pilot plant and simulation of a FBR. Roberto Galiasso Tailleur*, **1, Carlos Farina**, Sergio Rodríguez* and Sylvana Derjani-Bayeh* *Grupo TADiP, Departamento de Termodinámica y Fenómenos de Transferencia, Universidad Simón Bolívar, AP 89000, Caracas 1080, Venezuela, ** HyPro Consultant 4250 Corrine Dr., Suite 204, Orlando, Florida USA ABSTRACT

Continuous regeneration process was developed to treat a spent PtTiZrSO4/SiO2 alkylation catalyst with hydrogen in a Fluidized bed reactor. Catalyst that alkylated isobutane with olefins (C2= and C3=) in a pilot plant, accumulate soluble and insoluble-coke on surface in several passes through the system. It was regenerated in a small scale and in a pilot plant fluidized bed reactor (FBR.) Tests in semi-batch reactor generated data to develop the apparent kinetic rate and obtain the stoichiometry of the reaction. The information obtained in pilot plant was used to determine fluid dynamic correlations, a new set of kinetic rate constants, number of compartments in dense phase and catalyst efficiency factor, and to confirm the effects of operating variables. Simulations of the pilot plant and commercial size fluidized bed reactor were performed using three fluid dynamic models, the kinetic rate equation and the new fluid dynamic correlations. The effect of operating variables in alkylation cost were analyzed for a commercial size reactor and auxiliaries equips, integrated to the alkylation and fractionation stages of the process. The results indicated that apparent hydrocracking of soluble-coke follows an order one in soluble-coke and 0.5 in hydrogen in the range of 60 to 80% of coke conversion. Soluble-coke aged with the number of passes. Hold up, bubble size and frequencies, and solid backmixing measured in hydrogen at high pressure and temperature are different than those in air. A new sets of fluid dynamic equations were determined. The continuous operation of the pilot plant confirms the effect of operating variables in soluble-coke conversion. The best fit of pilot plant coke conversion was obtained using a model composed by one compartment at the inlet, 10 compartments for the bubble moving up, and two compartments in series for the dense phase; the last two zones are connected by a crossflow. The simulation of the integrate process, alkylation regeneration, determine that 533 K and gas residence time of 0.2 h produce the minimum alkylate cost. Alkylate cost is driven by the amount of soluble-coke formed and regenerated. Keywords: fluidized bed reactor, average bubble size, catalyst regeneration. Simulation, economic evaluation

1. Introduction

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The production of a “green” gasoline using solid alkylation process is one of the most challenging tasks due to catalyst deactivation. Different solid alkylation catalysts were developed and tested for butane alkylation of isobutene, but they required a continuous regeneration process to perform a stable and profitable operation. Solid acid catalysts deactivate rapidly due to deposition and buildup of heavy hydrocarbons (coke) on the catalytic surface. Typical catalyst regeneration processes are oxidative, but it destroys the activity of some acid alkylation catalysts likes ZrTiSO4. The partial recovery of activity results in high levels of catalyst consumption, making solid catalytic alkylation economically and environmentally unacceptable. The characteristic of carbonaceous deposits formed during solid alkylation and their regeneration at lab-scale reactor are different than in pilot plant and commercial-scale; that represent another difficulty in scale-up processes. Guisnet et al.1, Weitkamp et al. 2, Flego et al.

3,4

, through chemical analysis, concluded that

coke formed during iso-butane/butene alkylation on zeolite is composed mainly of highmolecular-weight and highly branched paraffinic molecules / oligomers / polymers with one or several double bonds. Querini5 studied several options to regenerate alkylation catalyst using different fluids (air, ozone, hydrogen, hydrogen peroxide); their best-proposed choice is ozone followed by hydrogen. Hydrocracking of carbonaceous deposits at elevated temperature and pressure is one way to regenerate the catalytic surface. This method was proposed by Union Carbide in 19756 and then by UOP in 19937, among others. Josl et al.

8

explored regeneration with H2 of zeolitic catalysts in gas phase at 1.5 MPa and temperatures close to 573 K; these authors reported that after regeneration, the carbon content was less than 0.1 % by weight, and the catalytic activity was fully recovered. Thompson et al.9 use supercritical isobutane to regenerate the spent USY catalyst. In addition, there are several patents, see for example Zhang et al.10, whose claim the used of continuous regeneration with solvent or combination of solvent plus hydrogen. In these references, the effluent of the reaction zone is withdrawn from the alkylation zone immediately upon its exit and is send downward to a fluidized bed or moving bed reactor. Alkylene process11 uses a liquid phase riser-reactor for alkylation with a solid catalyst similar in concept to FCC. A lock hopper system periodically transfers a portion of the catalyst to a thermal regenerator and back to the reactor. This catalyst movement concept is like this used in continuous reforming catalyst regeneration stage. No doubts that catalyst reactivation and regeneration are key steps in the


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Alkylation process, but regeneration is conditionate by the type of catalyst and operating temperature. In current process scheme (see Fig. 1), the alkylation take place in a slurry transport reactor (STR), described in detail in part I of this paper 12; the coke was accumulated on catalyst, in presence of hydrogen and Pt, in a slurry phase reactor. Slurry is transfer into an hydrocyclonestripper stage (HCS) where gas and liquid phase are removed from solids. At the bottom of HCS, the wet solid is contacted with hot hydrogen to evaporate most of the adsorbed hydrocarbons present in pores; the dried catalyst is deliver into the dense phase of a continuous regeneration stage. There, the solids recover most of its activity by hydrocracking and are sent back to the alkylation stage. The regenerator is a fluidized bed reactor (FBR), like those used in FCC process, but operating in hydrogen at high pressure and temperature instead of air. Small particles of solid leaving the top of regenerator, through two stages of gas-solid cyclones, are retained in a filter stage (bag house); gases are recompressed, purged and blend with a makeup of fresh hydrogen before being recycle-back to the reactors. The purged gasses are treated in a PSA unit in the refinery to recover hydrogen and hydrocarbons. The total pressure used in the regeneration zone is 1.4 MPa, select mainly to operate downstream a de-ethanizer column with maximum recovery of olefins. For simplicity delta of pressure through the alkylation, solid separation and regeneration equips were not consider here. There is extensive literature13-21 about design, control, simulation and optimization of FCC regenerator, which had evolved due to many challenges brought about by environmental regulations, product-quality demands, and economics. They will be used as reference here despite of differences in operating conditions and fluid dynamic between hydrogenregenerator (~543 K, 1.4 MPa) and air-regenerator used in FCC (~1000K, 0.241 MPa13.) FBR is seldom divided into almost three reactions regions for simulation; they are named: bubbles, freeboard and “dense region”14. Most of the models proposed for catalyst regeneration focus on the gas-dense region (i.e. two-phase model15-17); there is several models that describe the behavior of emulsion phase

18-20

considering two or several compartments (CSTR) in-series.

21

Kunii and Levenspiel also include a third phase, the cloud, in modelling the FBR.


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There is a lack of information of the effect of pressure and temperature in fluidization behavior under hydrogen around 563 K and 1.4 MPa. For that we included in this paper important information about fluid dynamics obtained in pilot plant that was needed to develop the reactor models and kinetic rate models. Catalyst regeneration kinetic rate model has been developed previously in a small-scale fluidized bed reactor study22 using one pass spent catalyst. The information is extended here in the same small-scale semibatch reactor but with catalysts that have several pass and amount of coke. The kinetic rate results were adjusted using a long-term test (FBR pilot plant); the kinetic rate model previously developed is simplified to cover only the 60 to 80% of coke conversion range. In pilot plant reactor, fluid dynamic was analyzed without reaction to determine the main parameter that affect the kinetic rate of reaction; the new sets of experiments are mainly dedicated to confirming the effect of pressure in the fluid dynamics and in catalyst deactivation. To be able to analyze the effect of operating variables in the cost of light alkylate ($/(octane.m3)) the regeneration process was simulated at commercial-scale and all equips dimensioned to determined capital and operating costs. Then, the integrated STR-HCS-FBRFractionation process was simulated for a BC operating conditions. Details of economical evaluation for the base case (BC) are presented in complementary information and the results of the impact of regeneration variables are discussed in term of cost of alkylate. 2. Experimental The methodology followed in this work is as follow: 1. Preparation and characterization of spent catalysts with several cycles alkylationregeneration and level of coke; 2. Test in semibatch small-scale FBR the above samples of spent catalysts to obtain the apparent rate of reaction, stoichiometry, effects of operating variables. Gases and solid samples were characterized; 3. Simulation of small-scale FBR to obtain the kinetic rate constants and stoichiometry; 4. Study of fluid dynamics of the pilot plant fluidized bed reactor at typical reaction conditions but without reaction; 5. Perform a “scouting” study in pilot plant to confirm the solid throughput needed in pilot plant to operate in steady-state;


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6. Perform long term tests (continuous operation) of pilot plant; 7. Simulation of continuous pilot plant operation using three fluid dynamics models; 8. Design a commercial-scale FBR for regenerating the solid produced in the STR-HCS using model fluid dynamics model III. Determined the Base Case (BC) operating conditions; 9. Simulation of the commercial scale FBR integrated to the STR-HCS and Fractionation stages to determine the relative impact of operating variables in the alkylate cost 10. Perform a sensitivity study using Model III. 2.1 Production of spent catalysts with several cycles Alkylation-Regeneration Alkylation and Regeneration of catalysts in pilot plants produced a large amount of spent catalysts with different cycles to be study in semibatch mode of operation in the small-scale and in the pilot plant FBR. Spent catalysts D10, D21 and D32 (superscript indicates the number of alkylation-passes and subscript the number of regeneration-passes) were regenerated to produce D11, D22 and D33 catalysts with different “ages” of coke, at 50% olefins conversion in alkylation and 80% conversion in regeneration stages. Spent catalyst with three cycles of operation and different levels of coke were obtained to develop the hydrocracking kinetic rate equation. (Table 1 depicts, as an example, the properties of D43 D10 and D32.) Mechanical stability of spent catalysts D43 (amount of “fines” particles formed per unit of time and changes in pore size distribution) were arbitrarily measured by fluidization of solid in nitrogen - doped with 150 ppm of water – that flow at 2 cm/s during 48 hours at 523 K, 4 MPa. 2.2 Kinetic rate study. 4 samples of spent catalyst with different level of coke (0.4 to 0.8 wt% from alkylation plan were used to study the effect of variables and develop the kinetic rate equation in the small-scale FBR operating in semibatch mode (continuous in gases, batch in solid.) The reactor geometry is described in ref

22

. Hydrogen, 81% of purity, is injected

trough a fritted plate (gas-distributor) in very small bubbles. Spent catalyst was fluidized in hydrogen at linear velocity of 0.2 cm/s, 400 K, 1.4 MPa. Then, to start the regeneration, spent catalyst was heated to desired temperature at constant pressure. Different temperatures (from 533 to 573 K), solid contact times (from 0.1 to 0.5 h), and catalyst particle sizes (50, 100 and 150 microns) were used. The sets of experiments generated one hundred and twenty-two samples of gases and solids that were automatic obtained at different operating conditions.


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Temperature inside of reactor were controlled within ±0.1 K and pressure within ±1 Pa. Gases leaving the reactor were analyzed by on-line GC-FID apparatus using a Carbowax 2230-type column and coke on samples of catalysts determined by micro-combustion in a Mc Bain microbalance (see detail in ref22.) Compositions of carbonaceous deposits on catalyst surface were characterized by H/C ratio, 13CNMR, adsorption of pyridine, and TEM analyses. Spent and regenerated catalysts, at different level coke conversion, were extracted by CS2 and the soluble hydrocarbons analyzed by GC-MS and

13

CNMR (see Table 2.) CS2-insoluble

carbonaceous were also characterized by solid 13CNMR and TEM techniques22. Results about the effects of different residence times, pressures and temperatures on carbon conversion, and gases produced are reported in Fig 2a. During the regeneration, 50 to 81% of total coke content is converted, thus, it remains some carbonaceous deposits on catalyst. Fig 2b compare selectivity and coke content on regenerated catalyst after one (R1), two (R2) and three (R3) passes through the alkylation-regeneration system at two temperatures and two particle sizes. The effect of temperature and particle size in gases produced is shown in Fig. 2 right Y-axis. 2.3 Simulation of small FBR in semibatch mode of operation. The small-scale reactor was simulated by solving the isothermal transient mass balance as a function of contact time; that predicted the change in coke concentration and gas produced by reaction as a function of solid residence time, temperature and pressure. The stoichiometry of the reaction (Eq. 1), kinetic rate expression (eq. 2), and constants were proposed to the simulation based on previous studies22. Previous results demonstrated that rate of regeneration slightly depends on coke composition in the range of 0.6-0.8% of coke content in spent catalyst. Thus, the new model used a simplify rate expression, only valid for the range 60 to 80% of coke conversion, but with constants determined with three-cycles catalyst. The fluid dynamic model used for the reactor is a well-mixed compartment for the dense phase and plug flow for the gases (see additional discussion in point 2.5.) A Runge-Kutta numerical method, programmed in VB6, was employed to solve the differential equations; it included a genetic algorithm (GA) subroutine that adjust the kinetic constants to fit the sets of experimental results. The GA adjust by mutation the constants until the sum of squared difference of predicted minus measured concentration of coke or gases is less than 1%. Mass and heat transfer gas to solid was neglected and the particle catalyst efficiency is adopted to 1 in these simulations.


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= [C12 H 23 ]Naph + 6.0 H 2 slow →  2C 2 + 2C 3 + 0.5C 4;

rreg = a ( g ) k o e ( − Ereg / RT ) (C10 + )C H0.52 ;

(1) (2)

The following well-known equations were uses for gas phase in plug flow mode carrying the gases out of the reactor: dN H 2b dN H 2b = −u b = K Hbe2 (C H 2,b − C H 2,e ) Vb dt dz

(3)

K Hbe2 ( N H 2,b − N H 2,e ) = rreg

(4)

K Hbe2 = 7.6(

ε mf ub De

)0.5 (5) db Similar equations predict each of gases (C2-C4) produced. Coke conversion is calculated by mass balance in batch reactor. Stability of the solution found by the GA was verified using different guessed value values (stating points) and checking the number of mutations and the final solution. rreg is the reaction rate (gmol C10+/liter h), k0,reg is the pre-exponential factor, Ereg. is the activation energy (kJ/mol.) C10+ and PH2 are the concentration of coke in solid and hydrogen partial pressure in gas; subscripts b and e stand for bubble and emulsion phases. The values of K Hbc2 (mass transfer bubble to emulsion) was obtained adjusting the K&L equation16 to hydrogen, at high pressure and temperature22. Lines in Fig. 2a represent the results of the simulation and points the experimental data. Catalyst regenerated in the small-scale was tested in a small alkylation reactor (see paper I12) and the results of activity reported in Fig. 2b. The bubble-regime in the small-scale FBR is completely different that commercial scale reactor. Thus, the kinetic constants found must be verified almost at pilot plant. 2.3 Fluid dynamic of pilot plant FBR. FBR dimensions (see detail in Fig. 3a) and operating conditions were: dp: 50, 100 or 150 microns, Ddp: 0.35 (m), Ldp: 1.61 (m), uo: 1-3 (cm/s); T: 513, 523, 533 and 563 K, P: 0.8, 1.4 and 1.8 MPa, Ts: 0.1, 0.2 and 0.3 h, Tg: 0.1, 0.2 and 0.3 h, Dfb :0.45 m, Lfb: 0.8m; a 7 holes perforated plate (gas-sparger); there is one stage internal cyclone (Dcycl): 0.08 m; db is for dense phase; b for bubbles; fb for freeboard. FBR is a pseudoadiabatic vessel. FBR fluid dynamics were studied without reaction in semibatch mode of operation (batch respect to the solid.) Minimum fluidization flow rates, bubble sizes, bubble density, solid


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content in the freeboard and solid residence times in dense phase were indirectly measured by deltas of pressure sensors (at gas-sparger, dense bed, interphase, cyclone zones), laser probes, and sampling of solid in the bed and in the freeboard. These measures were calibrated using a 3D cold model (data not shown in this paper.) Delta of pressure sensors and three high frequency laser probes were positioned along the high of dense phase and at interphase with freeboard to measure bubbles frequencies and sizes. The optical fiber probes measure frequencies of passing gas bubble (see Fig. 3b) in volume of less than 0.016 cm3 defined by three fibers-tips of 0.06 cm cross diameter. 5mm high sensitivity pressure differential transducers (AN221) were used to detected local change in pressure due to the bubble circulation (see details in 22.) Solid content and local backmixing were measured by injecting a fluorescent solid (catalyst impregnated with 1,1,1,4-tetraphenyl butadiene that emit a UV-blue light at 390 nm) and detecting the signal with the laser-probe22. In addition, isokinetic samplers measured the local concentration of traced and untraced solids (0.05 cm3 volume); all of probes and pressure sensors were placed at different radial and axial positions from 10 cm above the distributor to 10 cm below interphase emulsion-freeboard and from the center to 1 cm near the wall of reactor. More than 350 data points were obtained with each of these techniques; reconciliation procedure is described in reference22, which was used to obtain a coherent and reproducible data about average bubble size, particle concentration in the bed and qualitative solid backmixing degree. Fig 3c shows, as an example, the effects of pressure in bubble size and density obtained at two temperatures, two particle sizes at two levels in the bed. Bed viscosity were measured using Storm viscometer. High-speed camera, located at the interphase (dense phase-freeboard zone) provided an image of bubbles break rates. The information verified the bubble frequency at the top of dense phase. Solid local dispersion analyses of the fluorescent tracer provided information (not shown, but details can be seen in ref.22) about counter-current solid recirculation at 303 K and 1.4 MPa. Reactor model is important to determine the proper kinetic rate model. Eighty experiments without reaction were performed in the pilot plant FBR to check the effects of gas flow rates (uo: 0.1- 1.0 cm/s), particle sizes (40-60, 90-110 and 140-160 microns) and temperatures (533,543, 553 K) in fluid dynamic parameters. The results generated new correlations needed to simulate the reactor: average bubble size, solid content ACS Paragon Plus Environment

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in bubbles and interphase, delta of pressure at interphase, radial and axial distribution of solid particles, fines particles formation, solid distribution in freeboard, dense bed density and gases properties that are discussed in this paper. 2.4 Long term, continuous FBR operation. The previous described FBR was operated in semibatch (scouting tests and start-up) and continuous modes. The pilot plant reactor is pseudo-adiabatic. Wall temperature and gas inlet temperature was controlled using three electrical heaters. Temperature of catalyst in gas, cloud and wake are assumed those measured by internal reactor thermocouples (dense phase, gas inlet and outlet, 10 cm above gas-sparger and 10 cm below interphase.) Solid was added, in continuous operation, at rates between 0.05 to 0.1g/min of dry-spent catalyst from the top and withdraw at similar rate from the bottom using 2 Pa differential-pressure and two automatic rotating valves system (Fig. 2a.) Mass of gas and solid flow rates are recorded. Startup of continuous regeneration operation was performed by feeding hydrogen at 503 K (1.4 MPa) to fluidize 0.8 kg (inventory of solid) of spent catalyst in the reactor; the system was operated in semibatch mode until hydrogen reached a temperature 5 K below the selected steady-state-temperature; then catalyst was automatically added, the same amount withdraws each minute, and temperature adjusted. Hydrogen volumetric flow rate was kept constant for a residence time (Tg) of 0.2- 0.22 h. Dense and gas phase temperatures, gas frequency and delta of pressure were control until they were stabilized (around after 20 minutes). Average solid residence time (Ts) was set between 0.2 and 0.25 h. Temperature were controlled within ±0.1 K and pressure within ±1 Pa in the reactor. During transient (change of operating conditions) and steady-state operation, differential-pressure, temperature, gas and solid flow rates and bubbles frequencies were recorded; coke, in the hourly-samples of solid, were obtained by micro-combustion analyses. Steady-state is achieved when delta of pressure, bubbles frequencies, freeboard temperatures, coke and hydrogen concentration in regenerated solid are stabilized, period that were always less than two days Characteristic of regenerated PtSOxZrTi/SiO2 catalyst are reported in Table 1, as an example. Carbon at the inlet and outlet of the regeneration reactor were analyzed by micro combustion. Physico-chemical properties of catalysts were determined using the methods described in detail in paper I22. Fig. 4 shows the inlet and outlet coke content as a function of different operating conditions and particle sizes. Octane, particle size and operating condition are


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mentioned in the caption. 2.5 Simulation of pilot plant operation. The gases flow continuously through the reactor while the solid is continuously added and withdrawn at different points in dense phase during the transient and steady state operation. The flow-scheme of the FBR simulation program is describe in Fig. 5. The program solved the mass and heat transfer differential equations using a reactor model with two, three and four reaction zones; the model considers different amounts of solids in the gas distribution, dense bed and bubbles, as well as heat and solid transfer between phases (see model III below.) The numerical method solved the differential equations as a function of time on stream until the steady state is reached. In transient mode of operation, there are at least, two differential equations for the gas phase-wakes that are solved numerically by Runge-Kutte-Feldberg method as function of z, and two algebraic equations for dense phase by a Newton-Rawson algorithm; for gas phase there is two independent variable (z,T) and three dependent variables (CH2,b - CH2ce and δ.) For dense phase there is three algebraic equations with three dependent variables (CH2,ce, CH2,b and δ.) The inputs to the subroutines are the proposed apparent reaction rate expression (Eq. (2)), initial guess of kreg, Ereg and nH2 values, mass transfer rate constants between phases and the number of compartments in-series for gas (n) and dense (m) phases. The program calculated delta coke and hydrogen consumption for each of operating conditions and compare the results with experimental data. When square of difference in coke conversion and gases yields between the calculated and measured are higher than 1% (objective function), the program uses the genetic algorithm to adjust the kinetic rate constants, particle effectiveness factor, the stoichiometry and number of compartments reactor in dense phase. The program reports apparent kinetic rate constants, stoichiometry and numbers of compartments in series used for bubbles (n) and for dense phase (m) when converge. The catalyst properties for the model are resumed in Table 5 and the input parameter in Table 6. The general reactor balances for hydrogen in emulsion and bubble as a function length of axis (z) and time (t) are presented below using the same nomenclature than K&L model21. For hydrogen along the axis of reactor: ' t 0.5 In emulsion: dC H 2,e = η H 2 ak12,reg γ eCC10+ C H 2,c (1 − ε e ) ρ s (1 − δ ) − K ce (C H 2,b − C H 2,e )

dz

ue (1 − δ )


(6)

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In bubble

dC H 2 ,b dz

=

η H 2 ak12' , reg (γ w )CCt 10 + C H0.52 , w (1 − ε b ) − K bw (C H 2 ,b − C H 2 , w )

(7)

ub

and for hydrogen and coke in gas phase along the contact time:

dnH 2 dC dC dC = Fvo, H 2 (C Ho 2 − C Hf 2 ) − ( ∫ H 2 Vb ( z ) + ∫ H 2 Ve ( z ) + ∫ H 2 V fb ) dt dz dz dz ' for coke in solid C10t + = C100 + − (α1 ( ∫

(8)

dCH 2 dC dC Vb ( z ) + ∫ H 2 Ve ( z ) + ∫ H 2 V fb ) dt ) dz dz dz '

kreg Cc PH052 , p 1 1 3 − ] (10) and φ = [ with ηi = [ r DeffH 2 ( PH 2, g − PH 2, p ) φ tanh φ φ 1

(9)

(11)

Module (ϕ) is defined based on apparent rate of reaction in bubble - wake and in cloudemulsion zones; the kinetic rate constant k12' , reg is define per volume of phase and Deff was measured in a modified Wicke -Kallenback cell (see Table 1.) The global energy balance for the gas system assuming infinite rate of heat transfer between dense phase and bubbles (he-b). dT = dt

( Fgo (T o − To ) − Fgf (T − To ))ρCpg + ∆Hreg (∫

dCH 2 dC Vb ( z) + ∫ H 2Ve ( z) + rreg, fbV fb ) − UAex (Te − Tw ) dz dz ρVCp

(12)

Otherwise, equation (12) are solved including a term for heat transfer between dense phase and bubbles (he-b Ab(Tb-Te) in the numerator. The amount of hydrogen, coke, gases and temperature of bubbles-wakes in the FBR change as a function of time on stream (t) and the high of the reactor (z), when the reactor is operated in semi-continuous mode. Most of coke (present in wakes and cloud of bubbles) are hydrocracked flowing in plug flow mode along the reactor to reach the freeboard; then they return to dense phase going downward around the bubbles. Small amounts of solid, gases and heat are incorporated into the wakes during coalescence and break- up of bubbles phenomena, coming from emulsion and other bubbles; another small portion of solids, gases and heat leaves the wakes toward the emulsion due to the same mechanism. Internally, gases are also transfer to the wakes and into cloud-emulsion zone. Eq. (13), in Table 4, define the coke conversion and eqs. (14) to (18) use conversion to calculate the flowrates. Gas and solid velocities in dense phase are estimated with equations (19) and (20), δ with (21), bubble rise velocity with (22), porosity at fluidization with (23) and minimum fluidization velocity with (24). Equation (26) is used to determine the height (h) of


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the bed at any time, (27) to calculate the activity as a function of delta coke and (28) and (29) the rates of mass transfer. Freeboard efficiency is determined with equations (30) and (31) and enthalpies of gases with (32). w/wo is defined as the relative mass of solids in the bed, γb the fraction of the total bed occupied by bubble and εb the bubble porosity of bed; Equations (33) and (34) are used to calculate the cyclone performance. Bubble average size and solid content, obtained from pilot plant and cold model data, are estimated with equations (35) and (36). Equation (37) and (38) are used to calculate the bubble size along the bed. Rocket industries24 develop information for hydrogen properties (density, viscosity) in the range of 1 to 10 MPa and temperature up to 1000 K that largely differ to those measured for air. Gas phase properties are calculated at 563 K, 1.4 MPa, using hydrogen with 80% purity. Own-developed correlations and those published by American Petroleum Institute (1992) are used to calculated properties. They were compare with measured density and viscosity for gas phase a T and P. Fig. 6, left side, compares coke predicted versus measured and right side, the ratio of C2/(C2+C3+C4) gases predicted against those determined in pilot plant. The subroutines of the program plotted carbon on catalyst and gases as a function of axial position and contact time residence time. Other subroutines calculated the differences between predicted and measured values of conversion for different number of in series-compartments (n (gases) and m dense phase) used in model III. There is a special subroutine that perform a regression of fluid dynamic data to develop some correlations depicted in Table 4 (Eq. 25-38). 2.6 Algorithm to calculate volume or conversion of a commercial size regenerator Concepts and nomenclature of a simple two or three phases model used here for FBR was developed by Davison (cited in

21

), and then extended by Kunii and Levenspiel21, among

many other; recent advances were reviewed by Van Hommen and Mudde23 for FCC regenerator. Whether25 had described the methodology used for FCC regenerator scale up and heat transfer. Dadge and Puyade26 proposed a new model to simulate the FCC regenerator and Sun and Grace27 described the effect of particle size. De Souza Santos28 and MahechaBotero29, review different models for simulating the commercial units. All of them for airsolid system. There is no information published about hydrogen fluidization; thus, new sets of


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Energy & Fuels

correlations are needed to consider the important differences in gases properties at high pressure and temperature. Fluid dynamic and thermal behavior change with the reactor diameter and internals design. Authors disagree on the necessity of considering the spatial character of the bubble phase in the dense bed, but all agree that direct scale up of pilot plant results to commercial plant is not recommendable. Our previous experience in modelling commercial FCC’s regenerator using the simplest four-regions model of K&L (semiempirical model), and another more fundamental Eulerian-Eulerian continuous approach, demonstrate that the former approach is still very useful and simpler to simulate for steadystate operation. K&L model is easy to integrate in major optimization programs with minimum computational efforts, but need reliable kinetic rates and fluid dynamic data. We observe in simulating three commercial units that the contribution of the cloud-phase proposed by K& L and the use of one compartment reactor for the interphase area have small contribution in reproducing commercial unit data. In three revamping cases studies, just two compartment in-series reactors model for dense phase, a proper size for average bubbles diameter and the amount of solid crossflow (transfer from emulsion to wakes) were enough to optimize operational results at steady state. We obtained22 good results in predicting FCC regenerator results in steady-state operation using fluid dynamic model III. Assumptions. PtTiZrSOx/SiO2 catalyst is classified as type-A particles, according Geldart definitions21. Three fluid dynamic models are used to understand the economic impact of regeneration stages on alkylate cost with and without integration: I) Plug-flow in bubbles-wakes phase with average bubble diameter, one CSTR in dense-cloud phase. Gas and solid mass transfer between wakes and dense phase are not included; gas phase that perform as a plug flow in the freeboard, without reaction is included. II) Discrete numbers (n) of compartments (CSTR reactors) in series with variable bubble diameter for bubbles-wakes phase, one compartment (CSTR) in dense phase and unidirectional crossflow exchange between phases; a plug flow in freeboard phase that operates without reaction. III) One compartment in the gas-distributor zone (CSTR), n Compartment in series (CSTR reactors) with variable bubble diameter in bubble-wakes phase, discrete number (m) of compartments in-series (CSTR reactors) in dense phase-cloud and crossflow between


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bubble and dense phase. Plug flow model is used in freeboard that operates with or without reaction. FBR, Base Case (BC) operating conditions are: To: 538 K; PH2: 0.81 MPa and 80% coke conversion. Kinetic-rate parameters obtained with pilot plant and other inputs are specified in Table 6. The additional assumptions are: 1) Uniform radial distribution of bubble sizes and solids. 2) Coke in wakes and dense phase-cloud are continuous phases. 3) Average bubble size and solid content in bubbles are calculated with correlation developed from pilot plant data (Equation (35-36)). These equations have similar structure that those proposed by Morri and Wen30, but they were adjusted to hydrogen fluid dynamic. 4) Kinetic rate parameters determined in pilot plant are independent of fluid dynamic of the reactor. 5) Coke content on catalyst surface are treated as homogeneous continuous function. 6) Heat balance consider three different interconnected regions operating at different temperature, with vaporization of hydrocarbons and heat losses by the wall. 7) Regeneration reaction rate are limited by mass transfer between gas-wake and gasdense phase and in pores of catalyst. Model I: Plug flow for bubbles CSTR for dense phase. The simulation program (the flow scheme is depicted in Fig. 7) of commercial-size FBR using Model I solves point by point the two gas differential equations (4 and 40) along the high of the reactor, considering an average bubble sizes and solid content, together with two algebraic implicit equations (39 and 41) for dense phase. In the bubble-phase hydrogen is fed at To,reg and is heated by the wake heat of reaction and by heat transfer from cloud-emulsion along the bed (one or several compartments in-series). The heat balance included a small amount of heat lost by transfer at the wall (Q3) and the heat used to vaporize hydrocarbons coming in pores of catalyst (FHC λHC). Energy and mass balances for model I in steady state operation is as follows: Mass balances for bubble-wake: Equation (4) mentioned before


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Mass balance for dense phase:

0 = −ηH 2 ρsak12' ,reg(γ ce)CCm10+1+,ceCHm+21,ce,0.5 (1−εe )(1−δ ) + Kb,ce(CHm+21,b − CHm+21,ce) − ue (1−δ )(CHm+21,ce − CHm2,ce) / h (39) dTH 2,b ρ sηH 2ak12' ,regγ bwCC10+CH0.52,b (−∆H ) + hbc ab (TH 2,bf − TH 2,cef ) = Heat balance bubble-wake (40) dz At(δ )(FH 2,bCpH 2 + FS ,bCpS + FC 2 H 4CpC 2 H 4 ) Heat balance emulsion ηH 2ρsak12' ,reg(γ ce)CCm10+1+,ceCHm+21,ce,0.5 (1−δ )(1−εe )(−∆HH 2 ) − hb,ceab (Tcem+1 −TH 2,b )(εb ) −Q3 − λHCFHC (41) Tcem+1 = Tcem + At(1−δ )(FH 2,cCpH 2,C + FS,cCps + FC6Cp6 + FC2Cp2 )

Q 3( kJh −1m −2 K −1 ) ~ aext (Tav. )1.310 4

(42)

The total hydrogen consumption, and the correspondent soluble coke conversion, are calculated by addition the consumption in the two reacting zones. Subscripts

w

is used for

bubble-wake and e for cloud-emulsion phases respectively. Model I was used to simulate the effects of catalyst particle sizes due to its simplicity. The model is prepared to add crossflow. Design of freeboard for air-solid system is well described in the literature21,31-32. Here, the program simulates the freeboard using equations (43) and (44) adapted for hydrogen that are solved with a RKF numerical method. Entrainment of solids decreases with the height of the freeboard until it reaches the level specified for solid-content at the inlet of cyclones (input value in the simulation; efficiency E, Eq. (28)) Equation (31) calculates average concentration of solid above the dense phase produced by bubble bursts at interphase (solids are thrown as a clump into the freeboard but soon they fall back into the interphase.) The freeboard calculation is the same for the three models. Gases composition at the outlet of reactor is like those leaving the dense zone interphase with the freeboard. Kinetic rate constants, mass and heat transfer equations, cyclone efficiency and % of fines at the outlet information are used to determine the volume of freeboard using half of dense-phase gas linear velocity as criteria. The simulation model verified the coke conversion, and heat generated and lost in freeboard. The mass and energy balances are: dCH 2, fb

dz '

= q5 (η H 2 ak12' ,reg e q6 z CC10 + CH0.52,b )


(43)

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dTH 2 , fb dz '

=

q7η H 2 ak12' ,reg e q8 z CC10 + C H0.52,b ( − ∆H ) − Q1 FH 2 ,bCp H 2 + FS ,b e q8 z Cp S + FHC Cp HC

Page 16 of 56

(44)

Equations (4), (39) and (43) were solved using the following boundary conditions (model I and II) were z an z’ are the high (variable) of reaction zone and the freeboard zone. 0 z = 0, T = Tg0 ; CH 2 = CH0 2 ; CHC = CHC ;

dCH 2 = 0, Fs : 9.8mT / h; FC10+ = FC010+ : 0.8wt.%,; γ bw ( z) : 0.02; db = 8cm; (45) dR

f z = h, T = Tgf ; CH 2 = CHf 2 ; CHC = CHC ;

dCH 2 = 0, Fs : 9.4mT / h; FC10+ = FCf10+ = 0.16wt.%;γ bw ( z) : 0.02; db = 8cm; (46) dR

f z ' = h, T = Tgf ; CH 2 = CHf 2 ; CHC = CHC ;

dCH 2 = 0, FC10 + = FCf10+ ;0.16mT / h; Fs0, fb : 0.023mT / h dR

ff z ' = (h + h' ; T = Tgff ; CH 2 = CHff 2 ; CHC = CHC ;

dCH 2 = 0, FC10+ = FCf10 + ;0.16mT / h; Fs0, fb : 0.001mT / h dR

(47)

(48)

Similar boundary conditions applied for n compartments in models (II). Model three use a small compartment (CSTR) at the inlet that produces coke conversion under intense backmixing. Hence, coke content, gases and temperature at the inlet of first of n and m compartments are those living the distributor compartment. The efficiency factor ηi (eq. (10)) adjusts the rate of hydrocracking by mass transfer in pores of catalyst. Effective hydrogen diffusivity (Deff) and tortuosity (τs) factor, used to calculate the Thiele module, were measured with different levels of coke in the semibatch reactor. The diffusional control slightly depends on particle size and level of coke in the rnage of 60-80 % conversions. Mass and heat transfer rate constants to the solid (Kbw, Kbce, hb-w and hb-ce) were evaluated using equations (28 and 29) adapted to hydrogen from Werther25 equations. Notice that there is an equilibrium of temperatures between gas and solids in bubbles, and in emulsion.

Model II Model II consider variable sizes and number of bubbles along the axis, as well as their solid content in wakes. Bubbles grows at expense of dense phase receiving gases and solids at the outlet concentration from dense phase (crossflow.) Solid residence time in wakes increases respect to those calculated with constant size bubbles due the reduction of bubbles velocity


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Energy & Fuels

along the bed. The equations for gas phase (49-50) were solved for each of n compartments in series using a discrete calculations method because is stable and the changes can be tracked; the high of compartment may equal a discrete number of bubbles, or any other criteria adopted at the start of the simulation. In addition, there is one compartment (m: 1 CSTR) in dense phase (Eqs. (39-41).) The program also solved freeboard equations (43-44). The simulation is initiated by guessing the reactor volume and temperature, or conversion and temperature (values obtained with model I) and then to calculate this values by using the mass and energy balance equations. Assumed values were adjusted by successive iteration until differences between predicted and specified (objective function) conversion or reactor volume are less than 1%. The program estimates the number of compartments taking in account the volume of gas in bubbles (calculated based on gas frequency, local delta of pressures) as a function of times and positions, interphase rate of burst by sampling.) First compartment (n=1) use three to five times the high of the bubble (diameter dbo), the diameter of the reactor and εg to dimension the volume of this compartment (boundary condition); auxiliary concentrations and temperature are defined for nth of compartments to include crossflow. The properties before reaction are calculate taking in account inlet stream contribution to nth of n n' n' n' n' compartments ( FHn 2,b ; FHC , FCn10+ , FSn , Tbn ) plus the cross flow ( FHn'2,e ; FHC ,e , FC10+,e , FS ,e , Te ) from

cloud-dense phase to bubble-wake, minus those transferred back to the cloud-emulsion ( n' n' n' n' FHn'2,b ; FHC ,b , FC10+ ,b , FS ,b ,Tb ), see equations (53-65.) These rates of gases, solid and heat transfer

by crossflow (qg,e-w , qs,e-w, hg,e-w) reproduce the change in gas, solid content and temperature of the bubbles along the high of reactor. Then, the program solves the mass and energy equations with reaction for the nth of compartments using a guess value for n’th as input data n+1 to predict the outlet properties ( FHn+21,b ; FHC , FCn10+1+ , FSn+1 , Tbn+1 ) of this compartment. Similar

calculation continues until the accumulative volume or global coke conversion equal the volume or conversion specified. The amounts of solids that effectively incorporate in bubbles is discounted from the emulsion in several iteration procedures. When the difference between predicted and calculated reactor volume or conversion is higher than 1%, the program recalculated again everything using the last values as new guess. The mass and energy balances equations for gas phase are:


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+1 n +1, 0.5 n +1 0 = (η H 2 ρ s ak12' ,reg γ bnCCn10 + ,b C H 2 ,b − K b ,ce (C H 2 ,b − C H 2 ,ce ) +

n +1 b

=T + n' b

T

uo (C Hn +21,b − C Hn +21,b ) d pε b

+1 n +1, 0.5 n +1 ρ sη H 2 ak12' , reg γ b CCn10 − Te ) + C H 2 ,b ( − ∆H reg ) + hbc ab (Tb

=T + m' e

T

(50)

FH 2,b Cp H 2 + FS ,b Cp S + FC 2 H 4 CpC 2 H $

0 = −η H 2 ρ s k12' ,reg (γ c + γ e ) m CCm10+1+ ,eC Hm +21,e, 0.5 + K b ,e (C Hm +21,e − C Hn 2,b ) −

m+1 e

(49)

uo hε ge )

(C Hm +21,e − C Hm '2,e )

(51)

q4ηH 2 ρ s ak12' ,reg (γ c + γ e ) m CCm10+1,eCHm2+1,e,0.5 (−∆H H 2 ) − hb,e ab (Tem+1 − Tbn )(ε b ) − Q3 − λHC FHC FH 2,c CpH 2,C + FS ,c Cps + FC 6Cp6 + FC 2Cp2

Where: Vbn ' = Vbn + ∆Vb ;Ven' = Ven − ∆Vbn (53); γ bn +1 = γ bn (54), CCn10' + ,b = Vb γ b (1 − x4n ') + ∆Vγn b (1 − x5 ) n

n

Vb + ∆Vb

C Hn ' 2,b =

C

m' C10 + , ce

(55)

Vbnγ b (1 − 6 x4 ) + ∆Vbnγ bn (1 − 6 x5 ) (56), m ' Vbmγ bm (1 − 6 x4 ) − ∆Vbnγ bn (1 − 6 x5 ) (57) C = H 2 , ce Vbn ' + ∆Vbn Vbn ' − ∆Vbn V m (γ + γ e ) m (1 − 6 x4 ) − ∆Vbnγ bn (1 − 6 x5 ) (58), n ' = ce c Tb = Vbm ' − ∆Vbn

∑ F Cp + ∑ (q ∑ (F + q m

Tbm' =

(52)

i

i m

i

− qgm, w−e )Cpi

m g ,e − w

m g ,e−w

−q

m g , w− e

' i

)Cp

∑ F Cp + ∑ (q ∑ ( F + (q n

i

i n

i

n g ,e − w

n g ,e − w

− q gn, w−e )Cpi

− q gn , w−e )Cpi

(59);

(60); qeb = 2.1K ce−b ( uo − 1.8umf ) 0.3 (61), qs,e−w = qg,e−wws (62), dp

ub = uo − umf + 0.75gdb0.5 (63) fb =

6 At (uo − 1.8umf ) 3.14db3

(64) d (db ) = dz

3.14db4 (qg ,e−w − qg ,w−e ) (65) 18 At(uo − 1.8umf )

qg,e-w and qs,e-w are the rate of mass of gas and solid transfer from emulsion to the bubble per second per unit of bubble volume and ws is de fraction of solid (wt. per unit of wt. of gas in emulsion.)

Model III Simulation using Model III calculates the volume required for a given conversion, or the conversion for a given volume of reaction zone. Model III use one compartment for the gas distributor zone, n compartments in-series for gas phase (variable bubble size number and solid content), m compartments in-series for dense phase and crossflow. This model solves equations (49 and 50) together with equations (51 and 52). Here, we report the result of using


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Energy & Fuels

m=2, two compartments in series, as an example. For m=1, z: ςh (the initial value for h was previously obtained with model I), the program calculates the intermediate conversion and temperature using the inlet conditions, rate of crossflow and reaction; then for m=2, z: (1-ς)h the program calculates the final conversion and temperature using the output of previous compartment. Conversion, or volume, at the outlet of second compartment is compared with specified conversion or volume. If the objective function (predicted – specified values) is higher than 1%, the simulation program (Fig. 7) adopts another high for the compartments and recalculates conversion and temperature. Then the simulation proceeds to calculate the freeboard size using the specified maximum amount of particle at the inlet of cyclone (Fs,f, Table 6) and the interphase temperature. Some of the output of the simulation are depicted in Table 7. The same simulation program (Fig. 7) obtain the effects of temperature, residence time and particle size on delta of coke at constant reactor volume; some of results are reported in Fig. 8 and in Table 7.

2.7 Estimation of alkylate cost ($/octane m3). The effects of a percent change in any of operating variables in alkylate cost of FBR, at constant feeds throughput, alkylation and Fractionation equipment sizes, are reported here (percent deviation respect to BC value); that allow us to represent the impact of these variables in a relative way. The cost of alkylate (objective function) takes in account the cost of ethylene, propylene, and isobutene and the cost of operation for a plant integrated to an existing Gulf Coast refinery in 2014. The refinery provides olefins, isobutane, electricity, low quality hydrogen water and low-pressure steam, consider as cost (computed as cost), and receives high- pressure steam, low purity hydrogen, light alkylate and C2 stream from the process (computed as credit.) An empirical equation calculates the octane number based on compositional data of alkylate12; Solid alkylation-regeneration-fractionation plant of Fig. 1 was simulated by Rodriguez Dominguez (2005)33 and then updated in 2014 by current authors to evaluate the effect of some operating variables in the performance of the process. Gases and liquid properties were calculated using PROII (2008)34 database and equations. Price of feeds came from Platt's reports. Details about the economic evaluation are reported in complementary information.


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In the right part of Fig. 1 is shown the separation-recycling and compression part (mention here as Fractionation) of the plant that was simulate with PROII. The integrated simulation of the plant at given operating conditions (BC) define the size of equipment, utilities consumption and yields at different point in the process scheme (including hydrogen, water, steam, catalyst, olefins and iC4 recycles in each of equips.) The results of STR simulation provides the input for the FBR calculation, and the solution of the FBR generates the input data for the STR and for separation-recycling stages. Thus, simulation is complex and slow due to recycles effects. Preliminary information about recycles is introduced to the reactors simulation programs and then the results of the simulation manually fed to PRO II to calculate and adjust these recycled streams in an iterative process. After three recalculation passes through the process, the recycles values remain constants within the precision expected (±1.5%) for the cost of alkylate. Previous alkylation-regeneration study had defined that BC case must use 50% olefin conversion in alkylation and 80% of coke conversion in regeneration stage that represent a compromise between catalyst consumption, alkylate yield, coking of catalyst and loss of olefins. Separation and fractionation stages are like those of HF alkylation plant.

Table 8 resume the effect of main operating variables in alkylate cost. See complementary information for other simulation results. Capital and operating costs for BC, calculated using the methodology describe in reference35, are shown Table 9. Analyses of capital costs assume that the new plant located in an existing Gulf Coast refinery is constructed in two and half years. The working capital is fifteen percent of the total capital investment. The economic analysis assumes a seventeen years’ life, with straight-line depreciation and zero scrap value. The interest rate and tax rate are taken as twelve percent and thirty-four percent, respectively.

3. Results and Discussions 3.1 Mechanism of coke built up and aging on PtZrTiSOx/SiO2. Fundamental studies22 about regeneration of spent catalyst by hydrogen shows that hydrocracking reaction is promoted by Pt and the rate of reaction is dependent on hydrogen partial pressure. Rate of catalyst alkylation and deactivation depend on numbers of Lewis acid sites and hydrides available on surface; theses acid sites are in mesopores, and at the


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intersections meso-micropores soon covered by adsorbed heavy hydrocarbons (soluble in CS2 C10+- hydrocarbons mentioned as “soluble-coke”.) Most of these soluble-coke could be hydrocracked22 but some is aged into insoluble-coke after several cycles of operation. The current kinetic rate study was performed using catalyst with three cycles alkylationregeneration at different levels of soluble-coke. The catalyst after several cycles (D43, Table

1, second of columns) slightly accumulated non-regenerable coke content (polymericaromatics) and loss surface area, pores volume, acid sites, sulfur content, and activity respect to the catalyst of previous cycles. The soluble coke that were formed on spent catalysts D33 during the cycles has an average H/C ratio (by moles) between 1.15–1.19 and they are composed by 28% paraffinic and 68% naphthenic type compounds (Table 1, D33 catalyst); the rest of carbon are insoluble aromatics and polymerized hydrocarbons. CS2-extracts have a carbon distribution in the range of C10 and C16, with decreasing concentration as a function of molecular weight (Table 2.) Aging of coke occurred by dehydrogenation of naphthenes into CS2-insoluble aromatics that polymerize in situ. Naphthenes and polymers are preferentially located at meso-micropores intersection (causing pore mouth plugging) and in micropores. Catalyst activity after one, two and three cycles in alkylation-regeneration system (compare values for regenerated catalysts in Table 1) are reduced, while the amount of CS2-insoluble coke increases. 0.76 wt. % of coke was deposited on fresh catalyst (D) during 1st cycle in the alkylation pilot plant at 0.4 h of residence time and 363 K (52 % of ethylene conversion.) Spent D10 sample had a 2.9 ratio of (Naph.)/(Par.) in soluble-coke. Then, D10 was regenerated for 12 minutes at 523 K (1.4 MPa), producing average ratio of gases of 0.6 (C3/(ΣCi) or 0.51 (C1+C2/C4.) D11 sample had 0.11 wt. % of unconverted coke. D21 sample was obtained in a second pass through alkylation that form 0.79 % by wt. of coke at 51% of olefins conversion; 2.9 ratio of Naph./Par. ratio was measured in soluble coke. D22 were regenerated in hydrogen at 523 K, 1.4 MPa for 12 minutes, producing average gases with ratios of 0.59 for (C3/( ΣCi) or 0.52 for (C1+C2/C4); 0.13 % by wt. of coke remained on solids. Then, D32 was generated during the third pass through alkylation where it accumulate 0.81 % by wt. of coke with 3.1 Naph./Par. ratio. D33 was obtained by regeneration; the average ratio of gases produced was 0.47 for C3/(CT) or 0.54 for (C1+C2/C4); solids contained 0.15% by wt. of unconverted coke. Strong acid site (SAS) were also changed by the repeated cycles alkylation-regeneration as follow:


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D11 (1st Reg) SAS: 0.34; D22 (2d Reg) SAS: 0.31), D33 (3er Reg) SAS: 0.28) The results show that the higher the number of cycle, the higher the amount of insoluble coke and the lower the micro-porosity available for reaction on regenerated samples. The rate of regeneration logarithmic-decreased as a function of number of cycles p (see a function in equation (2)). The process requires a bleed of spent and a make-up of fresh catalyst to maintain the alkylation activity in the STR. The new sets of experiments update the previous kinetic rate determined for hydrocracking of coke using four cycles of catalyst alkylation.

Table 2 shows that alkylation activity of catalysts, obtained at different level of olefins conversions, decrease with the amounts of coke on aged catalyst D43,i. The higher the level of conversion in alkylation, the higher the amount of soluble coke-present on surface. Table 2 also shows, as an example, the analyses of extracted by CS2 hydrocarbons. Notice that the higher the conversion in alkylation, the heavier the soluble coke and the lower the paraffins/naphthenes ratio. That indicated how critical is the selection of the level of conversion in alkylation because more and more naphthenes and polyaromatics are formed on “aged” samples. Conversion of soluble-coke by hydrogen in the range of 533-563 K (1.4 MPa) proceed through hydrocracking of paraffins and cycloparaffins using Pt-activated hydrogen and not through hydrogenolysis of adsorbed hydrocarbons22. Analyses of gases show mainly C2 to C4 paraffins production (Eq. 1), with negligible generation of C1 and C5. Notice in Table 2 the carbon distribution in gases produced by aging of samples. Previous studies22, measured the rate of paraffins and naphthenic coke conversion; the results demonstrated that hydrocracking rate of paraffinic-coke is almost twice the naphthenic-coke. The rate of reaction become quasi-independent of the composition, in the range of 50 % conversion in alkylation and 60 to 80% coke conversion in regeneration, because mainly naphthenic-coke remain on surface. The rate of reaction was simplified using (Eq. 2.)

3.2 Semibatch reactor tests. The results of the tests in semi-batch mode of operation at different initial temperatures, hydrogen partial pressure and residence time demonstrated that higher the solid contact time, reaction temperature and hydrogen partial pressure, lower is the coke content in regenerated catalysts (see Fig. 2a, left Y-axis) and higher the accumulated gas produced (Fig 2b, right Y-axis.) The rate of carbon removal become very small, above 80% conversion because the “reactive” species are nearly completely converted, and the catalyst


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start to loss sulfur from the surface by reduction of active sites. Going beyond 85 % of conversion produces irreversible modification of active surface, with loss of sulfur and metal dispersion22; only carbonaceous compounds with very low reactivity, or inaccessible, remain on surface. 72% of carbonaceous deposits that remain on surface after 80 % conversion are CS2-insoluble (Table 1), 65% of them located in micropores. Hence, conversion (delta coke) must be limited to the range 0.7- 0.81 wt. % to reduce catalyst deactivation. Fig. 2a, left Yaxis, shows that the cumulative individual gas production arrives to a plateau when plotted against contact time in semi-batch reactor operation at two temperatures. Fig. 2b, left Y-axis) shows the activity of regenerated sample in alkylation as a function of three contact times (R1, R2 and R3) two temperatures and two particle sizes for D43 catalyst. The results confirm that the higher the contact time in regeneration, the lower the amount of carbon and the higher the catalyst activity recovered for both temperatures and particle sizes. Semibatch tests were repeated at different gas linear velocities (other operating variable kept constant) and the results shows similar coke conversion. The frequency of small bubbles did not change the backmixing of the small-scale reactor.

3.3 Simulation of small scale reactor. Small-scale reactor was simulated using a program like this of Fig. 5. The program assumed a simple fluid dynamic behavior: plug flow for bubbles, one CSTR for dense phase without crossflow, effect of gas distributor and freeboard conversion. The program uses 85 experimental point to confirm the kinetic rate expression and determine the kinetic rate constants. The algorithm converged in 12 CPU, after 6 mutations. The convergence does not depend on the guessed values and the solution is stable. The lines in Fig. 2a are predicted by the program. The comparison with the point indicated that in fit well the experimental results

Fig. 6 shows the predicted versus measured values of coke conversion (left Y axis) and gases produced (right Y axis). The program predicts values with deviation lower than ±2.1% (at 95% confidence range, skewedness of 1.34 (distribution is right-skewed.) The statistical analyses (ANOVA) of multiple sets of observations, including experimental error, shows that deviations are not randomly distributed in the range of conversion. However, the convergence shows a flat are of solution around the best values of constants.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Current semibatch regeneration data were employed to estimate the rate of solid addition and withdrawal in pilot plant for different operating conditions. Fluid dynamic of small scale cannot be scale up. Bubble size, degree of backmixing, mass and heat transfer are for this reactor and the model used may affected the kinetic rate constant values determined there.

3.4 Pilot plant FBR fluid dynamics. Fluid dynamic experiments were performed with fresh catalyst in presence of hydrogen (523 K, 1.4 MPa) and without reaction, to determine the minimum fluidization flow rate, solid content in bubbles and bubbles size distribution in the pilot plant (Fig. 3a). Data about frequency of bubbles, local delta of pressure were determined by micro sampling analyses and optical visualization at interphase; The hydrogen-fluidized bed reactor were operated in the range of 0.1 to 1.0 cm/s gas linear velocity. Consolidation of these information overcome the limitation of individual techniques of measure and allow to calculate axial average bubble size along the reactor. The methodology used here to transform frequency into bubble size was developed by Werther and Morelus (1973)36. For example, at gas linear velocity of 0.4 cm/s, an average bubble diameter of 7 and 10 cm was calculated for 10-20 cm above the gassparger level and for 10 cm below the freeboard level (543 K, 1.4 MPa, 0.8 % purity in hydrogen.) Fig 3b shows the frequencies of bubbles for these two points (see extreme value of segmented line that represent the deviation in five measures) for 50 microns and 0.6 cm/s of gas linear velocity; similar information was obtained in other axial and radial position. Fig.

3c shows an example of average bubble diameter for the lower and upper position and two particle sizes and three pressures. Maps of average bubble size were built-up for each average particle sizes and gas linear velocity (not shown). Equation (29), developed with these data, predict average bubble size along the reactor with a deviation of ± 0.14 cm (within 95% confidence range), valid in the range of gas velocity of 0.1 - 0.5 cm/s, temperatures of 533583 K, for average particle diameters 40 -170 microns22 and 1.4 MPa of total pressure. 10 cm above gas distributor, the average bubble diameter starts to grow linearly (Fig. 3d) without slugging and clustering. The value calculated for average bubble diameter (eq. 29) is 35% lower than those used by us to simulate a FCC regenerator, and 20-30% lower than calculated with equation developed by Kato and Wen (1969), Rowe (1976), and Mori and Wen (1975) (see their discussion about air solid correlation in reference19.) The uses of high pressure


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Yates36 correlation predict 18% lower bubble size. Number of bubbles, originally formed at gas-sparger zone (0-20 cm above the distributor), are fast reduced along the axis. More than 200 tests were performed to determine radial average number of bubbles and size of them, formed between distributor and 0.1 m high level; despite of experimental efforts, current probe methodology cannot provide a reproducible axial and radial bubble size distribution and number of bubbles in the gas-sparger region of reactor or detect bubble with diameter lower than 1mm. Nevertheless, above this region (0.1 m-1.44 m) the average bubble sizes and number of them, measured along the axis of reactor-core region, are reproducible (deviation respect to average diameter is ± 0.1 cm within 95% confidence range for 10 measures taken at the same axial position.) The average values seem quasiindependent of gas linear velocity, hydrogen purity and temperature used at these narrow ranges of operating conditions required in the regenerator. Fraction of gas in bubble slightly increases from the bottom to the interphase along the core of reactor due to crossflow. Fraction of gas in bubbles goes from 0.37 to 0.39 from the center to the wall at z: 0.10 m), and from 0.38 to 0.396 cm3/cm3 at z: 1.0 m. Delta of pressure per unit of length of reactor decrease in the core region from 0.06 to 0.02 MPa/cm. Local laser probe and delta of pressure sensors shows important reduction in number of bubbles. Smaller bubbles collapse to form larger and denser bubbles. Very few large bubbles burst at the interphase; gas density change from 0.12 (at the bottom) to 0.15 g/cm3 (at the top, see Fig. 3c, upper right Y-axis) due to the incorporation of more solids than gases by crossflow (transfer from dense phase to gas phase and vice versa) at different operating pressures. Previous measures show that at 543 K, 1.4 MPa and for 50 microns particles, dense phase has 24% higher density and 35% higher kinematic viscosity than air-solid at FCC regenerator operating conditions. Total delta pressure for the dense phase in pilot plant was 3.2 KPa with fluctuation of ± 21 KPa at 543 K, using 50 microns size particles. The delta of pressure at the interphase (between 10 cm below and 20 cm above) was 0.11 KPa with fluctuation ± 21Pa that correspond to three average bubbles per second that break-up at this level. For example, for 50- microns particles, drag coefficient is 0.6 at 543 K and 1.4 MPa instead of 0.45 used in air simulations (FCC operating conditions.) The high amount of solid present in the region above interphase level (short of cloud) is due to the lateral projection of particles by hydrogen


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bubbles when approaches to the interphase. The study of interphase shows more bubble roof stability in hydrogen at high-pressure than in air at FCC operating conditions. The irregular dome is randomly formed at the interphase displacing particles up with bubble nose; particles on the bulge are ejected more vigorously than those from wakes, as the bubble bursts. Solid at the side of the nose accelerate upward while the ones at the bottom decelerate, falling off towards the next bubble. Through this mechanism, the bubble nose-layer becomes thicker, heavier and their acceleration smaller until the bubble mass center arrives to interphase level. The wake of the leading bubble acts as interphase for the trailing bubble nose that accelerates through the channel opened; thus, leading bubble is catching the particles ejected by the leading bubble building a “dense” phase at interphase with high backmixing. The shape of the dome has a significant effect on the ejection of solids particles and in the solid backmixing in the upper part of the bed. The effect of particle size in fluid dynamics is small; for 50, 100 and 150 microns average particle diameter, umf is of 0.08, 0.09, and 0.12 (cm/s) and εmf of 0.37, 0.39, and 0.40 (-) respectively. 50 microns was used in 180 of experimental points obtained with reaction in semi-batch reactor mode of operation; the effects of particle sizes were determined from other 30 experimental points. Gas linear velocity explored ranged from uo: 0.4 to 0.8 cm/s, three times higher than the minimum fluidization velocity and eight times lower than the slugging regime. Since 2 heat exchangers; operating cost in the order: oleffins >> catalyst make up > hydrogen make up > electricity > water > labor. • Global simulation of the process demonstrated that the best combinatorial of operating variables are: 353 K (inlet temperature), O/iC4 ratio of 0.2, H2/HC of 0.03 and C2/C3 of 0 ratios in the STR, 1.5 m T/h of hydrogen at 543 K in HCS and 1.5 m t/h of hydrogen at 533 K at the inlet of FBR.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

• The sensitivity study confirms the impact of dense phase backmixing and crossflow. • The lowest alkylation cost is the associated to the amount of soluble coke produced and regenerated on surface of mesopores.

5. Acknowledgments The authors want to acknowledge the support of Simon Bolivar University, the FONACIT of Venezuela and HYPRO Consultant for their continuing support of the research Group and the experimental work of Jose Andretti Salva and Juan Peretti, who obtained the pilot plant data, built the reactor models and perform the simulation in ProII®.

6. REFERENCES 1. Pater J., Cardona F., Canaff C., Gnep N.S., Szabo G., Guisnet M., “Alkylation of isobutane with 2-butene over a HFAU zeolite composition of coke and deactivating effect”; Ind. Eng. Chen. Res. 38, (1999) 3822-3833. 2. Weitkamp J., Maixner S., “Isobutane/butene alkylation on a LaNaY zeolite. Characterization of carbonaceous deposits by CP/MAS 13C NMR spectroscopy”; Zeolites 7, (1887) 6-8 3. Flego C., Kiricsi I., Parker W.O. Jr., Clerici M.G., Spectroscopic studies of LaHYFAU catalyst deactivation in the alkylation of isobutane with 1-butene”; Appl. Catal. A 124, (1995) 107-115. 4. Flego C., Galasso L., Kiricsi I., Clerici M.G., “TG-DSC, UV-VIS-IR studies on catalysts deactivated in alkylation of isobutane with 1-butene”; Stud. Surf. Sci. Catal. 88, (1994) 585-591 5. Querini C.A., “Isobutane/butene alkylation: regeneration of solid acid catalysts”; Catal. Today 62 (2000) 135-139. 6. Chang-Lee Y. Union Carbide, “Isoparaffin alkylation process with periodic catalyst regeneration” (1975) US patent # 3893942. 7. Kojima M., Kocal J.A. “Regeneration of an alkylation catalyst with hydrogen”; US patent 5310713 (1993) 8. Josl R., Klingmann R., Traa Y., Gleaser R., Weitkamp J., “Regeneration of zeolite catalysts deactivated in isobutane/butene alkylation: an in situ FTIR investigation at elevated H2 pressure”, Cat. Comm. 5 (2004) 239–241. 9. Thompson D.N. Ginosar D.M., Burch K.C., Regeneration of a deactivated USY alkylation catalyst using supercritical isobutane; App. Catal. A: General 279(1-2), (2005), 109-116 10. Zhang S.Y.F., Gosling Ch. D, Sechrist P. A., Funk G. A. “Dual regeneration zone solid catalyst alkylation process”. US Patent 5,675,048 (1997) 11. Meyers R. A., Handbook of Petroleum Refining Processes, McGraw-Hill, New York, 2004. 12. C2-C3 olefins solid alkylation in the presence of hydrogen using a slurry transport reactor-hydrocyclone-regenerator system and PtSO4TiZr/SiO2 catalyst. I Pilot plant


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Energy & Fuels

studies and Simulation of alkylation reaction. Energy and Fuels xx (xx), (2017), xxxxxx 13. De-Lasa, H.I., Errazu, A.F., Barreiro E., Solioz, S. “Analysis of Fluidized Bed Catalytic Cracking Regenerator Models in an Industrial Scale Unit” Canadian J. of Chem. Eng., 59, (1981),549-553 14. Dagde, K.K.; “Development of models for the simulation of fluid catalytic cracking reactors”. PhD Thesis, Department of Chemical/Petrochemical Engineering, Rivers State University of Science and Technology, Port Harcourt (2009). 15. Krishna, A.S. and Parkin E.S., “Modeling the regenerator in commercial fluid catalytic cracking units”. Chem. Eng. Prog., 31(4) (1985) 57-62. 16. Elnashaie, S.S.E.H., Elshishini, S.S. (1993) “Digital Simulation of Industrial Fluid Catalytic Cracking Units – IV: Dynamic Behaviour”. Chem. Eng. Sci., 48, (1993), 567-583. 17. Rao, R.M., Rengaswarmy, R., Suresh, A. K., Balaraman, K. S. (2004) “Industrial Experience with Object Oriented Modeling FCC Case Study”, Trans Ichem E, Part A, Chem. Eng. Res. and Des., 82 (A4) (2004) 257 – 552. 18. Fryer, C. and Potter, O. E., ‘Experimental investigation of models for fluidized bed catalytic reactors”, Aiche J., 22 (1976) 38-43 19. Mireur J.P. Bischoff KB “Mixing and contacting model for fluidized bed reactor”, Aiche J. 13 (5) (1967) 839-842 20. Jafari R., Sotudesh-Gharibagh R., Mostufi N.; “Modular Simulation of fluidized bed reactor”. Chem. Eng. Technolog. 27(2), (2004), 123-129. 21. Kunii, D, y Levenspiel, O, “Fluidization Engineering”, John Wiley & Sons, Inc., U.S.A., pages 355-373 (1969). 22. Galiasso Tailleur R. and Peretti J., “Regeneration of PtTiZr SO4/SiO2 by Hydrogen”, Technical report, Texas A&M Colleges Station (2005-2006). To be published in Fuels J. (2017). 23. van Ommen J.R., Mudde R.F.; Measuring the Gas-Solids Distribution in Fluidized Beds - A Review”. Proceedings The 12th International Conference on Fluidization New Horizons in Fluidization Engineering (2007) 24. Oefelein J.C., and Yang V.; “Modeling High-Pressure Mixing and Combustion Processes in Liquid Rocket Engines”. J. of Prop. and Power. 14 (5), (1998), 843-857 25. Werther J., “Scale-up modeling for fluidized bed reactors” Chem. Eng. Sci. 47, 8 (1992), 2457–2462. 26. Dagde K.K, and Puyate Y.T., “Modelling catalyst regeneration in an industrial FCC unit”, Am. J. Sci. Ind. Res., 4(3) (2013), 294-305. 27. Sun G., Grace J. R., “Effect of particle size distribution in different fluidization regimes”; Aiche J. 38(5) (1992), 716-722 28. de Souza-Santos M. L. “Modelling and simulation of fluidized bed boilers and for carbonaceous deposits” PhD. Thesis University of Sheffield, UK. (1987) 29. Mahecha-Botero A, Grace J. R., Elnashaie S.S., Lim CL. “Advances in modeling of fludidized bed catalytic reactors: A comprehensive review. Chem. Eng. Comm., 196:11, (2009) 1375-1405. 30. S. Mori and C. Y. Wen Estimation of bubble diameter in gaseous fluidized beds pages Aiche J. (1975) 21(1) 109–115) 31. De Lasa, H. I. and Grace, J. R., The Influence of the Freeboard Region in a Fluidized Bed Catalytic Cracking Regenerator, Aiche J., 25 (6), (1979), 984-991.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

32. Stojkososki V., Kostic Z., “Empirical correlation for prediction of elutriation rate constants” Thermal Science, 7(2), 2003, 43-58.Rodriguez Dominguez S. “Simulation de un reactor de lecho transportado y un regenerador”. Bs. Thesis USB, Venezuela (2004) 33. Pro II. SimSci-Esscor's PRO/II software; release July (2008). 34. Turton R. Richard C, R.C., Wallace B. Whiting W. B., Joseph A. Shaeiwitz J.A., Bhattacharyya D., Analysis Synthesis and design Chemical Process (4th Ed.) Prentice Hall International series in the Physical and Chemical Engineering Sciences) 4th Edition ISBN-10: 0132618125 (2008) 35. Wherher J. and Morelus O. “The local structure of gas fluidized bed”. A statistical based measuring system”. Int. J. Multiphase Flow, 1, (1973) 103-122. 36. Yates J.G. “Effect of temperature and Pressure on gas solid fluidization”. Chem. Eng. Sci. 51 (2) (1996) 167- 205. 37. Li J., Kuipers J.A.M.; “Effect of pressure on gas–solid flow behavior in dense gasfluidized beds: a discrete particle simulation study”. Powder Tech.; 127, (2), (2002), 173–184. 38. Ye M., van der Hoef M.A, Kuipers J.A.M., “The effects of particle and gas properties on the fluidization of Geldart A”. Chem. Eng. Sci. 60 (2005) 4567 – 4580 39. Rüdisüli M., Schildhauer T.J., Serge M.A. Biollaz S.M.A., van Ommen J. R. Scale-up of bubbling fluidized bed reactors — A review”, Powder Tech., (2012) 217, 21–38. 40. Bukur D., Nasif N. ‘The effect of bubble size variation on the performance of fluidized bed reactors”. Chem. Eng. Sci. 40 (10), (1985), 1925-1933. 41. H. Hatzantonis, H. Yiannoulakis, A. Yiagopoulos, C. Kiparissides “Recent developments in modeling gas-phase catalyzed olefin polymerization fluidized-bed reactors: The effect of bubble size variation on the reactor's performance” Chem. Eng. Sci. 55 (2000) 3237-3259

Nomenclature a Ar;Afb aw Cc Cpi db dp Fi Fwi E0;Ec Ereg g h he-c he-b hw Hr

Catalyst activity [-] Section of reaction and Section of freeboard [m2] External area of reactor [m2] Coke concentration on catalyst Heat capacity gas liquid and solid [Jmol-1 K-1] effective bubble diameter [m] average particle diameter [m] Moles flow rate [ Tmole/h] Mass flow rate [m T/h] Solid content at the interphase and at the cyclones [kgm-2s-1] Activation energy of coke hydrocracking [KJmol-1] acceleration of gravity [mls] Height of interphase reaction-freeboard [m] Heat transfer between gas and dense phase [J m-2 s-1] Heat transfer between gas and dense phase[J m2 s-1] Heat transfer emulsion-wall [J m2 s-1] High of reaction zone [m]


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Energy & Fuels

Hfb ko,reg kreg Kb-ce Kb-c Kc-e PH2 Mcoke p PT PHC Q1 Q2 Q3 q3,q4,q7 q6;q8 R S/V t Tg Ts ub * ub ubr umf uo V4 V5 V6 Vs Vg W xc Z zfb

High of freeboard [m] Pre-exponential factor hydrocracking reaction [mols-1MPa-0.5] first order reaction rate constant [mols-l MPa-0.5] gas interchange coefficient between bubble and emulsion [s-l] Mass transfer bubble cloud [s-1] Mass transfer cloud emulsion [s-1] H2 partial pressure gas MPa molecular weight [g/mol] Number of passes through alkylation-regeneration stages Total pressure [MPa] Hydrocarbon partial pressure [MPa] Heat generated [kJs-1] Heat accumulated [kJs-1] Heat loss by the wall [kJs-1] Constants of mass balance equations (34-35,42) [-] Constants of mass balance equations (36-37,43) [-] Constant equation (42-43) [kg m-2s-1] gas constant [J/(mol K)] surface to voidage ratio [m-l] time [h] (semi-Batch) Residence time of gas [h] cont. FBR Residence time of solid [h] cont. FBR rise velocity of bubble gas [cm/s] bubble rise velocity in a bubbling fluidized bed [cm/s] rise velocity of bubble with respect to the emulsion [cm/s] minimum fluidization velocity [cm/s] superficial gas velocity [cm/s] Volume of gas phase [m3] Volume of emulsion [m3] Volume of freeboard [m3] volume of solid [m3] volume of gas [m31 Mass of solid [m t] coke conversion [-] Vertical distance in reaction zone [m] Vertical distance in freboard zone [m]

Greek letters ∆HH2 Heat of reaction [kJ/mol] ∆ volume fraction of bubble in the bed [-I εmf volume fraction of bed at minimum fluidization [-] Φv mixing factor of viscosity [-] Γ volume of solids in bubble phase divided by the volume of bubble [-I Μ viscosity [Pa s] Ρ density [kg/m31


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ηH2

Page 48 of 56

Catalyst particle efficiency for H2 [-]

Table 1: Catalyst properties Table 2: Hydrocarbon adsorbed on catalyst at different levels of coke content Table 3: Gases produced by coke hydrocracking at different temperature and particle size (7180 % conversion). Table 4: Auxiliaries equation for FBR simulation Table 5: Catalyst properties. Input to simulate commercial size reactor (base case) Table 6: Input data for FBR simulation Table 7: Output of FBR at given amount of coke, activity and temperature at the inlet Table 8: Simulation of the effect of inlet temperature Table 9: Example of capital and operating cost calculation (Gulf Coast 2010) Figure 1 Flow scheme for the solid alkylation-regneration process Figure 3 3a) Semibatch operation. Right axis. Effect residence time on C10+ conversion at two levels of pressures (0.8 and 1.4 MPa) and two temperatures (533 and 543 K); point are experimental values; lines are from Model III simulation; 3b) Y left axis upper level, gas produced as a function of residence time at (543 k 1.4 MPa). Lower level Temperature as a function of residence time (inlet conditions 533 K,1.4 MPa). Figure 2 2a) Pilot plant flowscheme. 2b) Bubble frequency at two levels in the reactor (pilot plant); 2c) Right Y-Axis Effect of gas linear velocity in bubble size at two temperatures and two catalyst particle diameters. Left Y-axis gas density at two levels in the reactor. 2d) Average bubble size distribution along the axis of reactor for three particle sizes. Figure 4 C10+ as a function of time on stream at different operating conditions. Left Y axis inlet coke content. Right Y axis outlet coke content Figure 5 Program used to calculate the kinetic rate constants from pilot plant data. Figure 6 6a) Left Y-axis C10+ predicted by the model III in continuous operation vs. measured at three levels of carbon content three temperatures and three particle size; 6b) Right Y axis. Gases predicted by the model III vs. measured ones. Figure 7: Right side three phases model scheme. Left side, program used to simulate the FBR commercial size reactor. Figure 8. Right Y-axis, Simulation of the effect of solid residence time on coke content at the outlet at two levels of hydrogen total pressure. Left Y-axis Simulation of the effect of solid residence time on alkylation catalyst activity. Table 1 Properties SO4= wt% H/C Surface area m2/g Particle 10-40microns diameter % Pore volume cm3/g Micropores volume cm3/g

D43 5.4 1.23 108 0.2 0.29 0.08


D11 5 1.08 190 0.1 0.39 0.12

D33 4.5 1.09 172 0.1 0.37 0.09

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Energy & Fuels

Tortuosity factor* % of 40-60 particle size microns Pyridine remain ads. 373 K µmol/g Carbon content % wt. Catalyst activity for alkylation** Coke soluble in CS2 (323 K) Insoluble coke wt% Naphthenic compound in coke % % of C12 in CS2-extract

0.86 98.4 0.14 0.81 0.23 0.38 0.012 70 45

0.98 98.2 0.28 0.14 0.82 0.1 0.015 11 0.05

0.93 98.1 0.24 0.18 0.79 0.08 0.02 14 0.03

*Measured by nitrogen diffusion in a Wicke-Kallenback type of cells; ** measured in semi-batch reactor at t=0 (363 K, 1.4 MPa)

Table 2 Catalyst D43,4 D43,3 D43,2 D43,1 Olefin conversion % 40 % 50% 60% 70% Total Coke wt. % 0.43 0.57 0.8 0.93 Extracted material 0.39 0.51 0.71 0.82 Type of HC extracted % wt. distribution C10 C11 C12 C14 C15 % of naphthenes % of paraffins

31 28 20 13 7 67 33 Table 3

Temperature K / % wt. Ethane Propane Butane Pentane

29 31 19 14 7 69 31

533/50 0.002 0.005 0.005 0.002

27 30 19 16 8 74 26

26 29 18 18 9 81 19

543/50 553/50 533/170 0.002 0.005 0.002 0.006 0.008 0.004 0.007 0.010 0.004 0.010 0.012 0.006

Table 4

FCoke,27 − FCoke,28 FCoke,27

(13)

FC5,55 = 0.22 X r ⋅ FCoke,27

(15)

FHydrogen,55 = FHydrogen,54 − 3 X r ⋅ FCoke,27

(16)

(17)

FCoke,28 = FCoke,27 (1 − X r )

(18)

(19)

us =

(21)

u b = u 0 − u mf + (0 .61)( gd b )

Xr =

FC4,55 = 0.44 X r ⋅ FCoke,27

ue =

uo − δub (1 − δ ) s

δ = 1 − exp− 4.22(uo − umf ) 

   ρ g .( ρ − ρ ). d g p g  

ε mf = 0,62

µ2

3 p

0, 03

 ρg    ρ   p

0, 03

(23)

(14)

FC3,55 = 0.22 X r ⋅ FCoke,27

αδub (1 − δ − αδ )

(20) 0.5

umf =

(d ) .[g.(ρ 212µ 2 2 p 0.22 g


P

− ρ G )].

3 ε mf 1 − ε mf

/ µ g0.2

(22) (24)

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

AS π .(6.V p / π ) = . AP AP 2/3

φ=

af =

1 − p2C10 +

(27)

ε m, f DH 2ub d b3

(29)

) 0.5

ρ 3 .5 g 0 .5 E0 = 3.07 .10 − 9 f 2.5 (u f − u mf ) 2.5 Adp µ

d b = 8(U o − U mf )

0.33

T

−0.2

P d

0.02 p

∫ ln zdz / h

d bn − d b = exp( −0.28h / Dr ) d bm − d dbo

+ 5.85

db

DH0.52,b g 0.25 d b0.15

(28) (30)

(B +C .Tr + D.Tr )

h fg = A(1 − Tr )

(33) 0.2

umf

(26)

E = E∞ ( E − E∞ )e3.6 Z

(31)

9 µDcycl . πNVin ( ρ s − ρ g )

w A p (1 − δ )(1 − ε mf )ρ p

K H 2 bc = 4.5

C10+

K H 2 ce = 6.7(

D50cycl =

h=

(25)

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2

(32)

2

∆P i( V) := 0.24⋅ ρ⋅ V

(35)

γ b = 2 *10 d

(37)

d dbo = 0.345 At (

6

0.14 p

(34) (36)

(δ g µ g )

1.23

u0 − umf nd

(38)

)2 / 5

Table 5 Catalyst Properties (base case) Coarse diameter, microns (PSD1) Broad range of particle (PSD2 Wt % fines (1-40) microns Density, ρ p m Tn m3 -1

Molecular weight, g mol Specific Heat, Cp J g-1K-1 Average micro-pore diameter Ǻ (BET) *Effective diffusivity Deff Gas (cm2/s) 533 K Solid effective conductivity, K eff Jm-2s-1K-1 *Tortuosity factor (-) Coke wt%

D43

D44

40-60 30-70 0.001

1-60 1-70 0.01

1.19

1.44

106 118 139+32.10-3T 5 8 -3 0.7x10 0.24x10-3 5.77 10-6 8.8 10-6 0.92 0.83 0.81 0.18

*Measured in a Wicke-Kallenback cells

Table 6

Parameter Input

BC

P (MPa) To,H2 (K) Lr/Dr (-) Lfb/Dfb(-) Uo cm/s Ut cm/s dbo / dbm (cm) εm (-) ρs (kg/L)

1.4 538 6 5 0.3 8.7 18.2 / 0.02 0.42 1.12


Page 51 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

ρg (kg/L) µg (poise) γb/γc+γe (-) Fs (m t/h) Kb-ce (s-1) WHC pore /Wcat wt. % Gas distribution hce-wall Wm-2K-1 hfreeboard Wm-2K-1 hce-b Wm-2K-1 Deff, H2 cm2/s

0.032 3.4 10-4 0.02/2.5 9.89 6.2 0.01 Bubble caps 95 12 44 1.2E-05

Table 7 FBR- Simulation Results base case Model I

Value

Outlet-inlet Temperature (K) of H2 Volume (V4+V5) (m3) Length (m) E (kg/m2.s) for ufb: 1.15 cm/s Volume of freeboard (V6) (m3) Catalysts Mass inventory (m t) Fs,f (m t/h) Catalyst activity (-) Conversion of coke (wt.) Bubble rise velocity ubr cm/s Minimum Fluidization velocity (cm/s) Maxima fluidization velocity (cm/s) Average bubble size (cm) Gas residence time Tg (h)

539-547 14 + 36 15.0 0.005 24.0 3.0 10.03 0.78 0.87 0.23 0.176 0.3 7.2 0.22

Solid average residence time Ts (h) C2/(C2+C3+C4) (-)

0.32 0.3

Table 8 Operating conditions

$/ (Octane m3)

Tg,BC, PH2,BC, 50 µm Mod I

25.00

Tg,BC, PH2,BC, 50 µm Mod II

24.65

Tg,BC, PH2,BC, 50 µm Mod III

24.25

Tg,BC -10 K, PH2,BC, 50 µm

24.85

Tg,BC+ +10 K, PH2,BC 50 µm

25.12


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Page 52 of 56

Tg,BC; PH2, 0.93 MPa, 50 µm

24.88

Tg,BC, PH2,BC, 100 µm Model I

26.17

Tg,BC, PH2,BC, 150 µm Model I

27.17

Table 9

Installed Cost Reaction zone (STR) (FBR HCS and other separators Fractionation zone Compressor and pumps STR FBR Heat exchangers STR FBR General service and storage Indirect capital cost Total capital (15 years 8000 h/y) Operating cost Raw materials 880 at $/m t Cost of capital plus interest Catalyst (0.08 m T/h) Utilities (steam, water fuel) Labor 4 shift Cost $/m3/octane alkylate.

MUSD 2014 7,820.00 4,890.00 890.00 12,900.00 2,340.00 3,450.00 2,534.00 1,850.00 6,234.00 4,720.00 49,938.00 $/h 53,368.00 1,326.2 8,200.00 1,800.00 2,200.00 25.05

*Most of equipment are in carbon Steel. **Low pressure steam cooling $4.0 / MMBtu, selling High pressure steam Heating $6.8 / MMBtu, Water Cooling $0.4 / ton Electricity is at 0.064 $/ kWh and Gas is at 8.3 $/ MMBtu at Gulf Coast 2014.

Figure1


Page 53 of 56

Simulate in STR and FBR programs

H 2 purge

V-105

V-106

T-102

E-102 10

13

12

33 14

E-103

M-102 HCS-102

31

V-103 1

E-105

E-106

49 V-110

T-103

7

44 45

55

28

47

46 V-111

E-104

De-butanizer

H2

42

F-101 M-101

TK-101

53

5

P-101 A/B

V-112 iC4,nC4

38

39

P-102 A/B

4

F-102

22

20

E-110 lps

40 6

19

41

Cat withdrawal

C-101 A/B

TK-102 i-C4,C4

iC4,nC4

18

54

2

,C3, ,C3=

43

17

lps

27

FBR-102

C-102 A/B

30

STR-101

Cat make up

TK-103

48

E-111

V-109

26

25 F-103

,C3+ C3=

35

De-propanizer

lps

11

V-108 E-108

16 V-107

37

36

E-107

34

V-102 15

8 HCS-101 3

To fractionation

32

V-101

E-101

Alkylate

E-109 50

cw

52

From main fractionation

51 E-113

E-112

P-103 A/B

0 8

T0: 543 K

0.8 T0: 533 K

0.6

543

0.4 T0g: 533 K

0.2

a)

a)

538 533

0.1 0.2 0.3 0.4 Ts h solid contact time (semi-batch)

To:543 K

80 70

To:563 K

0.3

60 50

b)

Figure 3


0.2

50 microns 150 microns

R1

R2

R3

0.1

Coke on cat. Wt%

Model III

C1

C2

Alkylation activity (-)

1.0

C3 C4

C1-C4 mol/h (1.4 MPa)

Figure 2

Tg (K)

Olefins feed

H2,C2,C3,C2=,C3=

22

C-103 A/B

H2 Make up

to main fractionator

29

24 F-104

V-104

Simulate in PRO II

23

9

Conversion of C10+ wt %

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Energy & Fuels

CSTR long term operation

0.3

0.8 0.7

533 K 0.8MPa 150 µ

0.2

0.1

523 K 0.8MPa 100 µ

533 K 0.8MPa 50 µ

0.6

533 K 0.8MPa 50 µ

543 K 1.8MPa 100 µ

533 K 0.8MPa 50 µ

0

0.5 0.4

0

5

10 15 Days on Stream

20

25

Figure 5 Operating conditions Load experimental data, Seed kd Ed n H2 adopt db

Calculate fluid dynamic parameter two phase model Solve the mass balance equations PF gas phase, 1 or f two CSTR dense phase (Newton Rawson) Calculate Ci

f ,exp f ,calc Objective function (CC10+ - CC10+ )

If OF>1%

If OF

Solid Catalyst Alkylation of C2âC3 Olefins with Isobutane in the

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