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Energy & Fuels 1998, 12, 320-328
Relating Feedstock Composition to Product Slate and Composition in Catalytic Cracking. 4. An Extended Pendant-Core Model for Gasoline Composition C. M. Sheppard,† J. B. Green,* and J. W. Vanderveen BDM Petroleum Technologies, P.O. Box 2543, Bartlesville, Oklahoma 74005 Received July 25, 1997
The pendant-core concept has been used previously to predict product slates from catalytic cracking. In this concept, alkyl side chains and analogous moieties are defined as “pendants”, which are attached to a cluster of aromatic and/or naphthenic rings which is referred to as the “core”. This work extends the pendant-core concept via a model which correlates feed composition (19 main component types determined by mass spectroscopy) to nine product subclasses (both gasoline and non-gasoline) by adding product distribution functions. These product distribution functions depend upon the feed component class (saturates, aromatics, and sulfur compounds) and upon the core-pendant ratio. For example, the production of light gas and coke increases with the core-pendant ratio since the probability of coke formation increases with core size and the average pendant chain length decreases as the proportion of carbon in pendants decreases. Using these component distribution functions, and the mass spectroscopic analysis of feeds, one can calculate anticipated yields of nine product subclasses: light gas, C3/C4 gas, light cycle oils, heavy cycle oils, coke, and gasoline range: paraffins, olefins, aromatics, and naphthenes. The product distribution functions were developed from data on four feedstocks. For the four feedstocks used in the correlation, plus a fifth feedstock, the predicted product quantities are within 2 wt % of the experimental values. The present form of the model does not address effects of polar (acidic or basic) compounds in feeds on product slate.
Introduction In their review of the relationships between fluid catalytic cracking (FCC) feeds and products, Letzsch and Ashton1 concluded: “Feedstock composition, which is the major variable affecting FCC yields, is even more important than operating variables or catalyst selection.” In particular, these authors emphasize hydrogen content as a limiting factor in potential yield of light products from a given feedstock. The importance of feedstock hydrogen content toward determining yields of fuels meeting current and proposed environmental regulations was addressed in a subsequent review.2 This paper is the fourth resulting from an ongoing project in FCC of heavy oils. Since the primary difficulty in application of FCC or other refining processes to heavy oils relates to differences in their composition relative to that of conventional crudes, the primary focus of the earlier papers was on relating feedstock composition to FCC product slate and product composition.3-5 † Chemical Engineering Department; Louisiana Tech University; P.O. Box 10348 TS; Ruston, LA 71272. Fax: (318) 257-2562. E-mail:
[email protected]. (1) Letzsch, W. S.; Ashton, A. G. In Fluid Catalytic Cracking: Science and Technology; Magee, J. S., Mitchell, M. M. Jr., Eds.; Studies in Surface Science and Catalysis, Vol. 76; Elsevier: Amsterdam, 1993; pp 441-498. (2) Magee, J. S.; Letzsch, W. S. In Fluid Catalytic Cracking III; ACS Symposium Series 571; American Chemical Society: Washington, DC, 1994; pp 349-371. (3) Green, J. B.; Zagula, E. J.; Reynolds, J. W.; Wandke, H. H.; Young, L. L.; Chew, H. Energy Fuels 1994, 8, 856-867.
The present paper extends the prior semiquantitative pendant-core model for relating feedstock composition to product slate5 to a set of product distribution functions which predict yields of light (eC2) gas, C3/C4 gases, light cycle oil (LCO), heavy cycle oil (HCO), coke, and gasoline range: paraffins, olefins, naphthenes, and aromatics. Yields of these nine product subclasses are related to feedstock composition as described by a mass spectrometric analysis which determines a maximum of 22 hydrocarbon and thiophenic sulfur types.6 One objective of the model is to enable comparison of product slates obtainable from raw feeds to those obtainable after upgrading at various levels of severity. Another is to provide a baseline product slate for a given feed to be used in the evaluation of FCC unit and/or catalyst performance. Owing to the importance of FCC toward overall gasoline production and refinery profitability,7 considerable prior effort has been expended on developing FCC process models.8-18 However, much of the published and unpublished work deals largely with effects of (4) Green, J. B.; Zagula, E. J.; Reynolds, J. W.; Young, L. L.; Chew, H.; McWilliams, T. B.; Grigsby, R. D. Energy Fuels 1996, 10, 450462. (5) Green, J. B.; Zagula, E. J.; Reynolds, J. W.; Young, L. L.; McWilliams, T. B.; Green, J. A. Energy Fuels 1997, 11, 46-60. (6) Teeter, R. M. Mass Spectrom. Rev. 1985, 4, 123-143. (7) Avidan, A. A.; Edwards, M.; Owen, H. Oi1 Gas J. 1990, 88(1) (Jan. 8 issue), 33-58. (8) White, P. J. Oil Gas J. 1968, 66(21) (May 20 issue), 112-116. (9) Pierce, W. L.; Souther, R. P.; Kaufman, T. G.; Ryan, D. F. Hydrocarbon Process. 1972, 51(5), 92-97.
S0887-0624(97)00122-9 CCC: $15.00 © 1998 American Chemical Society Published on Web 01/16/1998
Pendant-Core Model for Gasoline Composition
operating variables, design parameters, and catalysts, with only limited consideration of the effects of feedstock composition. Also, virtually all published models with significant emphasis on feedstock composition are limited to gas oil (i.e., distillable) feeds. Thus, there is a need for new correlations which are applicable to lowquality feeds with significant levels of heteroatoms and residual (>1000 °F) components. These correlations may be incorporated into existing process models or used as a basis for new ones. Most published FCC models are based on lumped reaction kinetics. Product slate and composition are calculated from specified feed characteristics and assumed reaction behavior and rates for initial and intermediate species. For example, workers at Mobil developed an extensive model based on 10 lumped parameters.10-14 One advantage of this approach is that product slate can be calculated over a wide range of conversion. A different approach is taken in the present work, however. In this case, a single product slate is calculated for conditions where maximum gasoline yield is achieved. This enables direct assessment of the ultimate economic value of the feed under a common operating objective: maximum gasoline yield. The calculation is based only on the relative proportion of light gas, C3/C4 and gasoline precursors, “pendants”, versus cycle oil, and coke precursors, “cores”, indicated by the mass spectrometric analysis of the distillable feedstock components. The pendant-core concept was advanced by Wiehe.19 One outcome of this concept is that the ultimate yield of low molecular weight products obtainable from a given feed using either thermal or catalytic cracking is predetermined by the proportion of peripheral structural constituents, termed “pendants”, to that of the condensed integral structural components, termed “cores”. The detailed structures of pendants and cores present do not greatly impact either product slate or composition, particularly for catalytic cracking where extensive molecular rearrangement takes place. The overall ratio of pendants to cores can be reliably estimated from hydrogen content or H/C ratio of feeds,19 which in turn relates back to the importance of feedstock hydrogen content mentioned in the first paragraph of this paper. The pendant-core approach is philosophically different from a detailed reaction kinetics approach, because of its generic viewpoint of feedstock structure. The approach taken by some is that FCC products represent the culmination of specific mechanistic pathways of thousands of individual feedstock molecules. Thus, the (10) Voltz, S. E.; Nace, D. M.; Weekman, V. W., Jr. Ind. Eng. Chem. Process Des. Dev. 1971, 10, 538-541. (11) Voltz, S. E.; Nace, D. M.; Jacob, S. M.; Weekman, V. W., Jr. Ind. Eng. Chem. Process Des. Dev. 1972, 11, 261-265. (12) Gross, B.; Nace, D. M.; Voltz, S. E. Ind. Eng. Chem. Process Des. Dev. 1974, 13, 199-203. (13) Jacob, S. M.; Gross, B.; Voltz, S. E.; Weekman, V. W., Jr. AIChE J. 1976, 22, 701-713. (14) Weekman, V. W. Jr. AIChE Monogr. Ser. 1979, 75(11), 1-29. (15) Larocca, M.; Ng, S.; de Lasa, H. Ind. Eng. Chem. Res. 1990, 29, 171-180. (16) Farag, H.; Ng, S.; de Lasa, H. Ind. Eng. Chem. Res. 1993, 32, 1071-1080. (17) Arbel, A.; Huang, Z.; Rinard, I. H.; Shinnar, R.; Sapre, A. V. Ind. Eng. Chem. Res. 1995, 34, 1228-1243. (18) Corma, A.; Wojciechowski, B. W. Catal. Rev.sSci. Eng. 1985, 27, 29-150. (19) Wiehe, I. A. Energy Fuels 1994, 8, 536-544.
Energy & Fuels, Vol. 12, No. 2, 1998 321
only way to rigorously model FCC is to weight each pathway by feedstock composition on a molecular basis. From this viewpoint, treatments such as kinetic lumping are approximations necessary to handle real-world feedstocks like gas oils. However, from the pendantcore approach, lumping is perfectly acceptable and thus will yield a rigorously correct result. That is, product slate composition will ultimately reflect only pendantcore ratio or in other words, feedstock hydrogen content. Numerous examples of the correctness, or at least the utility, of the pendant-core approach may be cited. One is the uniformity of isomeric C7 isoparaffin and C8 alkylbenzene distributions obtained from different feedstocks, as well as their similarity to predicted distributions.4,5 Another is the consistent ratio of benzene/ toluene/ethylbenzene/xylenes found for 100 gasolines (0.14/0.32/0.07/0.47).20 This consistency of isomeric distributions as well as calculated balances for monoaromatics in FCC feeds and products has led several authors to conclude that the majority of gasoline range aromatics are formed (from pendants) via cyclization and hydrogen transfer transformations.4,5,20,21 In all likelihood, aromatic formation occurs to fulfill the demand for hydrogen needed to form isoparaffins.5 Thus, the increased aromaticity of gasoline from more aromatic feedstocks21 results from their hydrogen deficiency, which drives cyclization and aromatic formation, rather than direct conversion of feed aromatics to product aromatics. The great similarity in nitrogen compound type and isomeric distributions in LCO from different feeds22 suggests that core rearrangement may also occur to yield consistent product composition. The prominent nitrogen types identified were indole, carbazole, and aniline homologs. Insufficient information was found in the literature to assess whether a similar consistency existed for hydrocarbon and sulfur types. At high FCC conversion, light and heavy cycle oils are composed largely of aromatic/naphthenic cores produced from pendant-core cleavage. The proportions of aromatic, naphthenic, paraffinic, and aromatic substituent carbon types in LCO and HCO are predictable from feedstock composition.13,14 Isomeric olefin distributions in FCC products approach those calculated from thermodynamic data.23,24 Since much of the gasoline range material is derived from these olefin intermediates, which are in turn produced via pendant cleavage, the consistency in isomeric distributions for gasoline range products may be a direct consequence of this uniformity achieved for intermediate isomeric olefin distributions. The overall proportions of gasoline compound typessaromatics, paraffins, olefins, and naphthenessare dictated solely by feedstock hydrogen content and catalyst efficiency/ selectivity. For example, basic nitrogen compounds decrease catalyst efficiency and thereby cause an in(20) Yatsu, C. A.; Keyworth, D. A. Prepr.sAm. Chem. Soc., Div. Pet. Chem. 1989, 34, 738-749. (21) Van Klink, A. J. E. M.; Hartkamp, M. B.; O’Connor, P. Prepr.sAm. Chem. Soc., Div. Pet. Chem. 1989, 34, 728-737. (22) Dorbon, M.; Bernasconi, C. Fuel 1989, 68, 1067-1074. (23) Cady, W. E.; Marschner, R. F.; Cropper, W. P. Ind. Eng. Chem. 1952, 44, 1859-1864. (24) Bailey, W. A., Jr.; Sartor, A. F. In Advances in Petroleum Chemistry and Refining; McKetta, J. J., Jr. Ed.; Wiley-Interscience: New York, 1962; Vol. 5, pp 211-252.
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Table 1. Mass Spectroscopy Results for Neutral Compound Types in >650 °F Resids from Five Crudes (wt %) crude compound type saturates 0-ring 1-ring 2-ring 3-ring 4-ring 5-ring
formula CnH2n+2 CnH2n CnH2n-2 CnH2n-4 CnH2n-6 CnH2n-8
core (%)
Brass River
Lagomedio
Maya
Wilmington
Merey
0 24 40 53 65 75
22.4 13.7 10.6 10.6 6.0 1.4
11.0 15.2 11.0 6.5 2.8 0.2
10.1 12.0 8.1 5.7 2.4 0.0
0.0 8.8 10.5 10.8 14.4 2.3
4.8 14.0 12.3 8.5 4.2 0.3
64.7 42.3 97.7
46.7 35.7 68.9
38.3 28.2 54.9
46.8 46.8 131.3
44.1 39.3 82.4
3.1 3.1 2.9 3.4 4.4 6.3 3.9 3.5 1.5 0.2
4.0 2.8 2.7 2.8 4.0 6.1 5.2 4.2 2.1 1.1
4.8 3.8 3.0 2.5 3.5 4.2 4.3 5.2 3.3 3.6
1.3 3.9 4.6 6.7 6.2 6.3 4.1 5.7 3.0 2.5
4.4 3.5 3.7 2.9 4.5 6.0 4.7 4.8 2.6 2.2
32.3
35.0
38.2
44.3
39.3
0.1 1.7 1.2
0.6 8.3 9.3
0.6 13.2 9.7
1.2 5.4 2.4
1.0 8.0 7.3
3.0
18.2
23.5
9.0
16.3
100.0
99.9
100.0
100.1
99.7
total saturates total naphthenic saturates RNTa aromatic hydrocarbons alkylbenzenes benzocycloparaffins benzodicycloparaffins naphthalenes naphthocycloparaffins/biphenyls naphthodicycloparaffins/fluorenes triaromatics tetraaromatics
CnH2n-6 CnH2n-8 CnH2n-10 CnH2n-12 CnH2n-14 CnH2n-16 CnH2n-18 CnH2n-22 CnH2n-24 CnH2n-28
23 37 53 37 45 48 52 66 73 82
total aromatic hydrocarbons sulfur compounds thiophenes benzothiophenes dibenzothiophenes
CnH2n-4S CnH2n-10S CnH2n-16S
24 32 45
total sulfur compounds total a
See text.
crease in gasoline olefin content.25 Also, catalysts with small unit cell size increase gasoline olefin content because they contain fewer acidic sites (less hydrogen transfer).26 For the purposes of the calculations outlined below, only alkyl and cycloalkyl substituents are classified as pendants. Naphthenic moieties associated with aromatic systems, e.g., tetralin and 9,10-dihydrophenanthrene, are classified as cores. All aromatic moieties are classified as cores. The only cores assumed to enter the gasoline fraction are single aromatic or naphthenic rings, e.g., from alkylbenzenes or alkylcyclohexanes. In certain cases, selected products were assumed to form preferentially from one or more compound types in the feed. These assumptions were based on degree of fit obtained from feed/product correlations. Experimental Section Methodology for feedstock analysis and FCC has been described previously.3-5 Briefly, each feed was cracked at 521 °C (970 °F) using a Davison XP series equilibrium catalyst at a catalyst/oil ratio of 8.5 ( 0.5/1. A bench-scale FCC unit was employed; approximately 35 g of catalyst and 4 g of oil were charged per run. The yields of crude products (gas, liquid, coke) were determined gravimetrically. Gas chromatography (GC) was used to determine gas composition; GC simulated distillation (ASTM D2887) was used to determine proportions of gasoline (C5-430 °F), LCO (430-650 °F), and HCO (6501000 °F) in the whole liquid. GC/MS was used to determine (25) Green, J. B.; McWilliams, T. B.; Sturm, G. P., Jr. Prepr.sAm. Chem. Soc., Div. Pet. Chem. 1995, 40, 681-684. (26) Habib, E. T., Jr. Prepr.sAm. Chem. Soc., Div. Pet. Chem. 1989, 34, 674-680.
paraffin, olefin, naphthene, and aromatic subclasses in the gasoline range of each liquid. For this work, >650 °F neutral fractions (rather than whole >650 °F resids) were employed throughout in order to simplify feedstock analysis and modeling. Neutral fractions were prepared by passing whole resids through ion-exchange resins which remove polar (acid and base) compounds.27 Future versions of the model will include effects of polar compounds on FCC yields and gasoline composition.
Results Table 1 summarizes results from the mass spectrometric analysis of five feedstocks. Data for three of the feeds (Brass River, Maya, Wilmington) were published earlier.5 Results for the other two (Lagomedio, Merey) will be discussed in detail in subsequent reports. The data shown in the table are limited to neutral compound types since the current version of the mass spectrometric method considers only the types shown and normalizes their distribution to 100%.6 Calculation of the core percentage shown for each compound type was based on assumed structural characteristics and an average molecular weight close to 350. These assumptions were discussed earlier.5 For saturated hydrocarbons, the total ring-number weighted factor (RNT) was calculated as follows:
RNT ) S1 + 2S2 + 3S3 + 4S4 + 5S5 where S1, S2, ..., S5 are wt % of 1-5 ring saturates, (27) Green, J. B.; Hoff, R. J.; Woodward, P. W.; Stevens, L. L. Fuel 1984, 63, 1290-1301.
Pendant-Core Model for Gasoline Composition
Figure 1. Summary of mass spectroscopy results for neutral compound types in >650 °F resids from five crudes (wt %).
respectively. It should be noted that RNT includes weight contributions from both pendants and cores. A summary of the feed class distributions from Table 1 is pictured in Figure 1. It is instructive to compare the shape of the feed class distributions to the shape of the product yields shown in Figure 2 (along with the model results to be discussed later). The crude order is consistent between the figures. Notice that for the feeds (Figure 1) the saturates and sulfur compounds have a U shape and the aromatics a Λ shape. For the products (Figure 2) the C3/C4 gas, paraffins, olefins, naphthenes, and HCO have a U shape while the light gas, aromatics, LCO, and coke exhibit a Λ shape. These and other trends are shown quantitatively in Table 2, which shows coefficients calculated from correlations of selected feedstock parameters in Table 1 with yields of product subclasses obtained from catalytic cracking each feed under prescribed conditions noted in the Experimental Section. Product distributions from cracking Brass River, Maya, and Wilmington feeds have been published3-5 and the Lagomedio and Merey results are in preparation. The correlation coefficients were calculated from the four feeds (i.e., Brass River, Lagomedio, Maya, and Wilmington) for which experimental work had been completed at the time. For each feed class (e.g., 0-ring saturate) separate correlations of core, pendant, and total were attempted; in addition correlations were sought to the sums of all pendants and sums of all cores. A positive value for the correlation coefficient indicates a direct relationship between a given feed component and product subclass with +1.00 denoting a perfect correlation. Conversely, negative values imply an inverse relationship, and zero denotes no correlation. For example, formation of C3/C4 gas components as well as gasoline range paraffins and olefins correlated directly with 0-ring saturate content (n- and isoparaffins) of feeds (0.93, 0.98, and 0.97 correlation coefficients, respectively). Conversely, strong inverse
Energy & Fuels, Vol. 12, No. 2, 1998 323
correlations between 0-ring saturates in feeds versus gasoline range aromatics, LCO and, to a lesser degree, coke formation were obtained (-0.93, -0.98, and -0.79 correlation coefficients, respectively). The correlations judged to be the most significant are highlighted in italics in the table. As expected, strong positive correlations of total feed pendants with C3/C4 gas, gasoline range paraffins, and gasoline range olefin products were observed. Similarly, strong inverse correlations of these same products with total feedstock cores were observed. Gasoline range naphthene production correlated well with several feedstock parameters related to naphthenic contentsnotably total naphthenic saturates or naphthenic cores, RNT cores or pendants, or total saturate cores. Gasoline range aromatics yield correlated best with total aromatic content of feeds, but reasonably well with total cores. In contrast, HCO yield correlated best with total saturates or pendants from naphthenic saturates in feeds; it correlated negatively with sulfur compounds in the feeds. These results are consistent with the presence of a significant proportion of unconverted, relatively saturated compound types in the HCO. The negative correlation of HCO yield with sulfur compound types in the feed suggests complete conversion of sulfur compounds to non-HCO products (e.g., LCO, coke). Not surprisingly, coke production correlated well with feedstock aromatic hydrocarbon and sulfur compound content, and negatively with feed saturate content. An additional factor to be taken into account with respect to feed/product correlations is the effect of core size on the ability of a given compound type in the feed to produce a given product. For example, for feedstock components where a large proportion of the total carbon is tied up in the core (e.g., 5-ring saturates or tetraaromatics), the probability of a single pendant containing enough carbons (g5) to enter the gasoline range is low. On the other hand, the potential product slate for paraffinic (0-ring) saturates is essentially unrestricted. Table 3 shows the relative distribution of each compound type in the feed to the nine product subclasses. The developed relative distributions are based on significant correlations indicated in Table 2 as well as on product distribution functions based on core size (% core) of major compound types in the feed. As noted earlier in conjunction with Table 1, “% core”, simply reflects the average proportion of the total mass in a given compound type tied up in the core. The percentage of mass as pendants is 100% - (% core). A simple, albeit incomplete, way to envision the function of the fluidized catalytic cracker catalyst is that it frees the pendants from the cores. The pendants, depending on their length, contribute to the light gas, C3/C4 gas, gasoline, and some cycle oil. If these pendants scavenge a hydrogen atom they will be paraffinic (e.g., isobutane gas), otherwise they may form either olefinic or cyclic compounds. The cores, depending on their size, contribute to the cyclic (naphthenic) and aromatic gasoline plus cycle oils and coke. The simplest scenario would have all the pendants going into the production of gases and gasoline and all the cores going into the production of cycle oils and coke. The evidence
324 Energy & Fuels, Vol. 12, No. 2, 1998
Sheppard et al.
Figure 2. Pendant-core model product slate predictions compared to experimental results (wt % feed). Table 2. Correlation Coefficientsa Calculated for Product Slate versus Feedstock Composition for Brass River, Lagomedio, Maya, and Wilmington Feeds gasoline feed
componentsb
0-ring saturates total saturates total naphthenic saturates RNT total aromatic hydrocarbons
total sulfur compounds
total cores total pendants
products
light gas
C3/C4 gas
paraffins
olefins
aromatics
naphthenes
LCO
HCO
coke
pendant total core pendant total core pendant total core pendant total core pendant
-0.78 -0.96 -0.25 -0.93 -0.44 -0.25 -0.72 -0.21 -0.15 -0.33 0.73 0.80 0.60
0.93 0.75 -0.23 0.96 -0.02 -0.23 0.35 -0.27 -0.34 -0.15 -0.96 -0.99 -0.90
0.98 0.74 -0.28 0.97 -0.09 -0.28 0.26 -0.32 -0.38 -0.21 -0.98 -0.99 -0.93
0.97 0.80 -0.19 0.99 0.00 -0.19 0.33 -0.23 -0.29 -0.12 -0.95 -0.97 -0.89
-0.93 -0.66 0.35 -0.93 0.14 0.35 -0.24 0.39 0.45 0.27 0.99 1.00 0.94
-0.34 0.44 0.98 -0.05 0.99 0.98 0.86 0.98 0.96 0.99 0.44 0.33 0.59
-0.98 -0.76 0.20 -0.95 0.07 0.20 -0.17 0.22 0.26 0.14 0.86 0.86 0.84
0.40 0.94 0.72 0.65 0.83 0.72 0.92 0.69 0.65 0.77 -0.26 -0.36 -0.10
-0.79 -0.96 -0.24 -0.94 -0.43 -0.24 -0.71 -0.20 -0.14 -0.32 0.74 0.81 0.61
total core pendant
0.76 0.71 0.79
-0.37 -0.30 -0.41
-0.35 -0.28 -0.39
-0.43 -0.37 -0.47
0.26 0.18 0.30
-0.77 -0.81 -0.75
0.43 0.38 0.47
-0.99 -0.97 -0.99
0.75 0.70 0.78
0.59 -0.60
-0.89 0.89
-0.93 0.93
-0.89 0.89
0.94 -0.94
0.59 -0.59
0.84 -0.85
-0.10 0.10
0.61 -0.61
n a The correlation coefficient is a statistical measure to determine the relationship between two properties: F x,y ) ∑j)1(xj - µx)(yj µy)/nσxσy. b See Table 1.
does not support this simple of a model, but the model was a useful guide in the correlation development. To fit the component distribution functions, Microsoft’s Excel spreadsheet solver function (which uses successive quadratic programming) was used to minimize the user supplied objective function (i.e., the sum of absolute values of the difference between the nine measured and calculated product yields). The component distribution functions were constrained by a 100% feed utilization constraint (i.e., for a given feed 100% must be distributed between the products). In addition, the amount of “pendant products” (i.e., C3/C4 gas,
paraffins, and olefins) was compared, as a guide, to the feed molecule pendant percentage. To ensure smooth functions, nine quadratic relationships (with respect to core percentage) were assumed for the saturate feed types. Each aromatic component distribution function was taken to be a ratio of the corresponding saturate function. The sulfur component distribution function was taken to be an offset ratio of the saturate function. For example, the C3/C4 gas component distribution shown in Figure 3 decreases as the core size increases, as a smoothly decreasing function was supplied. The optimization routine set the aromatics component dis-
Pendant-Core Model for Gasoline Composition
Energy & Fuels, Vol. 12, No. 2, 1998 325
Table 3. Relative Distributions (wt %) of Feedstock Compound Types to the Nine Product Subclasses gasoline components feed compound type saturates 0-ring 1-ring 2-ring 3-ring 4-ring 5-ring aromatic hydrocarbons alkylbenzenes benzocycloparaffins benzodicycloparaffins naphthalenes naphthocycloparaffins/ biphenyls naphthodicycloparaffins/ fluorenes triaromatics tetraaromatics sulfur compounds thiophenes benzothiophenes dibenzothiophenes
core (%)
light gas
C3/C4 gas
paraffins
olefins
aromatics
naphthenes
LCO
HCO
coke
0.0 24.0 40.2 52.6 65.1 74.7
0.0 0.8 2.2 3.8 5.7 7.4
22.9 16.7 12.3 8.7 5.1 2.2
39.4 25.9 17.2 11.0 5.9 2.3
9.9 6.8 5.3 3.3 1.8 0.8
6.8 10.7 14.3 17.7 21.5 24.7
0.0 3.3 6.1 8.6 11.5 13.9
0.0 14.7 17.8 16.3 11.5 5.6
21.0 21.0 19.7 19.0 16.5 14.1
0.0 0.0 5.0 11.5 20.5 29.1
22.7 37.1 52.5 36.9 44.6
0.8 1.9 3.8 1.9 2.7
21.7 16.7 11.1 16.7 14.0
20.4 14.4 8.7 14.5 11.6
8.1 6.0 3.9 6.1 5.0
13.9 17.3 21.8 16.8 19.1
2.6 4.7 7.3 4.6 6.1
16.4 20.2 18.7 20.2 20.2
16.4 15.2 13.6 15.7 14.5
-0.2 3.6 11.0 3.5 6.8
47.7
3.1
12.9
10.4
4.5
20.2
6.5
19.8
14.2
8.3
52.0 65.7 73.4 81.7
3.7 5.8 7.2 8.9
11.3 6.2 3.2 0.0
8.9 4.5 2.2 0.0
3.9 2.1 1.1 0.0
21.6 26.8 30.0 33.7
7.2 9.8 11.4 13.3
18.9 12.8 7.4 0.0
13.7 11.8 10.6 9.3
10.7 20.2 26.8 34.8
24.0 32.0 44.9
11.6 12.2 13.9
8.1 6.0 2.4
9.6 5.7 0.0
4.6 3.9 2.9
13.4 15.5 19.2
1.1 1.6 2.4
14.0 16.9 18.1
1.2 0.6 0.0
36.4 37.6 41.0
tribution function to be in this case 128% of the saturate function. The sulfur compound function was manipulated by the optimization routine to be multiplied by 99% and offset by -8%. For light gas and coke, increasing functions with respect to core size were supplied; for the C3/C4 gas, gasoline components, and HCO, decreasing functions were supplied; and for the LCO, a function with a maxima was supplied. The optimization was constrained such that the total given component distribution was less than 100% and free to change the functions’ shapes. Constraints preventing negative component distribution values were added as needed. The starting point also had an affect on the results. In light of this, the optimization was initially converged using only nine distribution functions (i.e., setting the ratios to 1 and the offsets to zero). This solution was judged unacceptable. The solution was relaxed (i.e., some product yields were reduced so that the totals were less than 100%) and the optimization repeated including the ratios and offsets as adjustable parameters. The converged results did not utilize all the feed components due to the experimental results totaling less than 100%. Thus, upon approaching a solution, lower bounds were added to the nonunity component distribution totals and the optimization continued. The final results were obtaining by manually adding the remaining few percent. Figures 3-8 show distributions of each compound type as a function of core size. Data points in the figures correspond to relative distributions in Table 3. The increase in light gases with core size (see Figure 3) is consistent with the model of the fluidized catalytic cracker catalyst disassembling molecules (since the larger the core the smaller the average pendant) and, the higher relative partitioning of sulfur types to light gas (eC2) is in accordance with the significant correlation coefficient (0.79) noted for these types in Table 2. This contribution from sulfur compounds is higher (perhaps due to the sulfur forming H2S) by roughly 10% (MWH2S/MWcore ) 34/350). The total pendants correlate very well to C3/C4 gas, paraffins, and olefins (see Table
Figure 3. Light gas and C3/C4 gas production (via pendant liberation) as a function of core percentage.
2). The pendant to C3/C4 gas correlation coefficient is 0.89, and a nearly linear relationship between the two was found (see Figure 3). The relationships of gasoline range paraffins and olefins are decreasing and nearly linear with core size (see Figure 4). The much lower yield of gasoline range paraffins from sulfur compound types can be rationalized from the additional hydrogen required to form H2S liberated during cracking of sulfur types, which favors the formation of olefins or other unsaturated types. The
326 Energy & Fuels, Vol. 12, No. 2, 1998
Figure 4. Paraffinic and olefinic gasoline production (via pendant liberation) as a function of core percentage.
Sheppard et al.
Figure 6. LCO and HCO production (via core detachment) as a function of core percentage.
Figure 7. Coke production (via core detachment) as a function of core percentage. Figure 5. Aromatic and naphthenic gasoline production (via pendant liberation) as a function of core percentage.
cores are expected to partition largely into the cyclic products; the smallest cores are likely to end up in the gasoline (aromatics into the aromatic cut and naphthenes into the naphthenic cut) with the intermediate cores forming the cycle oils and the largest forming coke.
Correlation coefficients for gasoline range aromatics and naphthenes in Table 2 clearly pointed to their formation from pendants liberated from aromatic and naphthenic feedstock components, respectively. Thus, in Table 3 and Figure 5, notable formation of those subclasses from the respective feedstock types is indicated.
Pendant-Core Model for Gasoline Composition
Figure 8. Cumulative product distributions for the three feed classes (a, top) saturates, (b, middle) aromatics, and (c, bottom) sulfur compounds.
LCO yield correlates moderately with the proportion of feed aromatics and with total cores. LCO production curves contain strong maxima with core size for all feed types in Figure 6. Owing to their relatively high boiling point per unit weight, most of the larger aromatic cores fell into the HCO (650-1000 °F) rather than LCO (430650 °F) boiling range. Figure 6 also shows HCO product distributions. Feed saturates make a significant contribution to HCO, which decreases with core size. A strong correlation between total saturates and HCO yield was evident in Table 2. In all likelihood, these saturates represent largely unconverted material originally present in the feed. Aromatic hydrocarbon and sulfur compounds also decrease with core size and contribute less than the saturates to the HCO yield (the sulfur compounds contribution is very small). Not surprisingly, Figure 7 shows that coke formation increases with core percentage for all types and that the sulfur components in the feed overall make a large relative contribution to coke. For example, about onequarter of the tetraaromatic hydrocarbons in feeds went to coke and over one-third of the sulfur compounds go to coke. The strong correlation with aromatic feed cores is expected, based upon the aromatic core having the
Energy & Fuels, Vol. 12, No. 2, 1998 327
highest positive correlation coefficient (0.81) shown in Table 2. The appreciable formation of coke from sulfur compounds is in accordance with the usual sulfur content of coke.3-5 The partitioning of saturated cores to coke was higher than initially anticipated, but may be reasonable in light of the coke formed from cracking feeds comprised of 100% saturates such as pure hexadecane.18 Figure 8 (a-c) summarizes information in Figures 3-7 through the cumulative product distributions shown for all nine product subclasses from each general compound type in feeds. Table 4 and Figure 2 compare calculated versus experimental yields for product subclasses for the four feedstocks used to derive the above correlations plus a fifth feedstock (Merey) used as a test case for the model. The totals included for the experimental data were not normalized; for totals of the calculated data the slight deviations from 100% are the result of truncation. For the four feedstocks used in correlation, agreement between calculated and experimental data was within the error range estimated for the experimental data3-5 with a standard deviation of about 1% absolute. The Merey test case is basically within this range for light gas, C3/C4 gas, olefins, naphthenes, and coke, but outside this limit for the gasoline range paraffins, aromatics, and cycle oil products. The Merey gasoline analysis is biased from a recent changeover in GC/MS data acquisition software which resulted in a systematic shift toward increased apparent isoparaffin content and decreased aromatic content. This shift results from the increased data acquisition speed of the new software. Apparently, the old software systematically underestimated the area of intense narrow peaks such as the early (C5-C6) eluting isoparaffins. Discussion The current component distribution functions are an improvement over the previous correlation.5 The component distribution functions are smooth functions of core size whereas the old model was based on the discrete partitioning of molecules based upon the number of rings (e.g., g4 rings formed coke and light gas). Also, the current correlation predicts the yields for nine products (i.e., light gas, C3/C4 gas, paraffinic gasoline, olefinic gasoline, aromatic gasoline, naphthenic gasoline, LCO, HCO, and coke) versus four product classes (i.e., C3/C4 gas + gasoline, LCO, HCO, and coke + light gas). Thus, the product slate is much better characterized (e.g., it should allow the subsequent calculation of vapor pressure and octane numbers). Due to the complexity of the feed and process, approximation still remains in this or any other model. For example, the approximation that the molecular weight is 350 for all component types is noteworthy. In reality, the molecular weight is a separate distribution for each component type.28 As one examines each of the different feed classes (i.e., saturates, aromatics, and sulfur compounds) the average molecular weight will typically increase with increasing ring number or degree of aromaticity within each class. However, since the assumed molecular weight is used only in calculation (28) Boduszynski, M. M. Energy Fuels 1987, 1, 2-11.
328 Energy & Fuels, Vol. 12, No. 2, 1998
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Table 4. Pendant-Core Model Product Slate Predictions Compared to Experimental Results (wt % Feed) Brass River
Lagomedio
Maya
Wilmington
Merey
component
model
expt
model
expt
model
expt
model
expt
model
expt
light gas C3/C4 gas paraffins olefins aromatics naphthenes LCO HCO coke total sum of absolute error
2.6 14.3 19.4 5.8 15.1 5.0 12.7 17.5 7.5 100.0
1.7 13.9 19.2 5.8 15.0 5.9 12.4 17.6 7.2 98.7
4.4 12.3 15.2 5.1 16.2 4.8 14.7 14.3 12.7 99.9
3.5 12.6 15.6 4.9 16.2 5.3 14.7 14.0 11.5 98.3
5.2 11.4 13.8 4.9 17.1 4.9 14.4 13.0 15.5 100.0
5.2 10.8 13.2 4.3 18.2 4.2 14.4 11.8 15.6 97.7
4.5 10.1 10.9 4.0 19.1 7.2 15.7 14.8 13.9 100.1
4.4 9.8 10.0 3.7 20.0 7.1 15.7 15.5 13.9 100.1
4.5 11.4 13.4 4.7 17.2 5.5 15.4 14.2 13.3 99.7
4.7 12.7 14.8 4.8 16.5 5.5 13.5 12.3 14.6 99.4
3.4
4.1
of core percentage, the component distribution functions (Figures 3-7) will not be greatly affected by this approximation. Furthermore, the fitted product slates (Table 3) are more or less independent of the assumed average molecular weight. Another approximation is the mass spectroscopy analysis method itself, which considers a maximum of 22 hydrocarbon and sulfur types. Obviously, for >650 °F resids, a multitude of hydrocarbon and polar types are ignored using this procedure, which normalizes the 22 types to 100%. For the neutral fractions used in this work, the inherent limitations of the MS method did not severely impact the results. However, for whole resids, the model will have to be expanded to include explicit accounting for polar (acid and base) compound types. The component distribution function correlations were guided by the simplistic view that the FCC catalyst disassembles molecules. As the molecule’s core grows in size, the distribution shifts from the core producing mainly gasoline (naphthenes from cycloalkanes and aromatics from the aromatics) and LCO to more HCO and coke. Also, with growing core the pendant size decreases and the pendant shift from production of
5.7
3.3
8.9
gasoline size paraffins/olefins to greater levels of light gases. In the current version of the model, the three major feed classes are treated separately. This allows for refinement of the product distribution functions for each type. Potentially this approach could be extended to other types, e.g., nitrogen types. The best possible model is the one which accurately reflects product slates actually produced by each compound type in the feed. As more experimental data become available for feedproduct correlations, they will be used to further improve the model. Acknowledgment. The authors thank Ray P. Anderson for technical review of the manuscript. They also thank Maryann Greulich and Susan Howard for their help in preparing the manuscript. Funding provided by the U.S. Department of Energy under contract No. DEAC22-94PC91008 and via Association of Western Universities summer research fellowships were essential to the work’s completion. EF970122L
