Flash Points of Hydrocarbons and Petroleum Products: Prediction and

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Flash Points of Hydrocarbons and Petroleum Products: Prediction and Evaluation of Methods Sara Saad Alqaheem, and Mohammad-Reza Riazi Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b02669 • Publication Date (Web): 01 Mar 2017 Downloaded from http://pubs.acs.org on March 2, 2017

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Flash Points of Hydrocarbons and Petroleum Products: Prediction and Evaluation of Methods Sara S. Alqaheem* and M. R. Riazi† *Kuwait Oil Company, Kuwait (email: [email protected] ) †Department of Chemical Engineering, Kuwait University, Kuwait (email: [email protected]) *Corresponding author: Sara S. Alqaheem

ABSTRACT: Flash point of hydrocarbons and petroleum mixtures is an important safety related data for processing and handling of these materials. In this paper experimentally measured data on flash points of about 140 pure hydrocarbons and petroleum fractions were collected and used to evaluate existing methods for prediction of this data available in the literature. The errors for the available methods varied from 1.6 to 4.9% for pure hydrocarbons and from 3.7 to 11.1% for petroleum fractions. In these methods parameters such as vapor pressure, boiling point, molecular weight, density, activity coefficient and composition were used. Based on the available methods and simplified relations for vapor pressure prediction, it was found that the ratio of flash point to the boiling point of hydrocarbon systems and their mixtures is a constant and value of this constant is about 0.7 when both temperatures are expressed in absolute degrees. Average absolute deviation (AAD) for this simplified method was 1.7% for pure hydrocarbons and 2.8% for petroleum fractions which is comparable or better than existing methods. 1. INTRODUCTION The flash point specification is one of the major safety data items specified in typical Material Safety Data Sheet (MSDS). Flash point of hydrocarbon compounds (or their mixtures) is defined as the minimum temperature at which vapor pressure of the hydrocarbon is sufficient to produce the vapor needed to ignite the hydrocarbon with the air at the presence of an external source, i.e., spark or flame.1 Flash point is an important parameter for safety considerations especially during production, processing, storage and transportation of volatile petroleum products and fuels (i.e., LPG, naphtha, gasoline, diesel)2,3 as well as non-petroleum fuels such as coal-derived fuels and biofuels in a high temperature environment.4,5 It indicates the fire and explosion potential of a fuel. A low flash point fuel is a higher fire hazard material.2 Flash point should not be mistaken

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with other properties related to volatility such as flammability limit, auto ignition temperature, fire point and vapor pressure.

There are two main classes of techniques used to determine flash points of liquids: closed cup and open cup.6 The closed cup apparatus implies that the cup into which the liquid is placed is closed until the ignition source introduced and thus no vapor can escape. The open cup apparatus means that the cup is open to the air and the vapors can escape in the surrounding environment away from the flash point apparatus. Therefore, the closed cup flash point of a substance is generally lower than the open cup flash point often by several degrees.6 ASTM D93 describes the test method to determine flash point of petroleum fuels by Pensky Martens closed cup method. Most predictive methods and reported data in the literature are based on the ASTM D-93 test method. In this paper various methods of flash point prediction are evaluated with collected data on flash points of both pure hydrocarbons and petroleum products and then a new and simple predictive relation is derived based on the available methods and literature data.

2. EXISTING PREDICTIVE METHODS

Over the period of 1950s to 2000s for five decades more than a dozen methods have been reported in the literature for estimation of flash points of hydrocarbon systems and petroleum fractions. These methods are briefly introduced here. One of the earliest predictive methods reported by Butler et al.7 is a linear correlation of flash point (ASTM D 93) with boiling point.8

T = 0.683 T − 119

(1)

where TF and Tb are closed cup flash point and boiling point in °F. In another method proposed by Butler et al.7, it was observed that values of vapor pressure at flash point multiplied by molecular weight are relatively constant with average value of 15.19 lb/in2. For a mixture of hydrocarbons, Butler et al.7 assumed that each hydrocarbon exerts a vapor pressure equal to xi Pivap and proposed the following relation:


2

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Σ x MW P =

15.19

(2)

where xi is a liquid phase mole fraction of compound i, MWi is the molecular weight and Pivap is the vapor pressure of component i in psi at flash point temperature. This relation for pure compounds reduces to: MWP = 15.19. In 1971, another simple relation for estimation of flash point of hydrocarbon mixtures from vapor pressure was proposed by Walsh and Mortimer and presented in ASTM MNL50.1 T = 231.2 − 40 log P

(3)

where Pvap is vapor pressure at 100 °F in bar and TF is the flash point in K. For simplicity, Reid vapor pressure may be used instead of true vapor pressure.

In 1973, a simple technique for determining the approximate flash point temperature of a compound with the knowledge of only its atomic composition and boiling point was developed by Prugh9 from experimental data with some theoretical consideration as following: T = 1.4420 − 0.08512 ln CST T

(4a)

where TF is flash point and Tb is normal boiling point both in K, CST is the stoichiometric concentration in vol% of the vapor in the air and should be calculated by the following relation:

CST =

83.8 % 4C + 4S + H − X − 2O + 0.84

(4b)

C, S, H, X, O are the number of carbon, sulfur, hydrogen, halogen and oxygen atoms in the substance.


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Another method was developed by Riazi and Daubert10 relating flash point of petroleum fractions to 10% ASTM D 86 distillation in the following form: 1 2.84947 = −0.02421 + T T% + 0.0034 ln T%

(5)

where TF is flash point in K and T10% is the normal boiling point for pure hydrocarbon and distillation temperature at 10% vaporized for petroleum fractions in K.

In 1988, a general correlation was proposed by Patil for estimation of closed cup flash point of organic compounds from their normal boiling points.11 T = 4.656 + 0.844 T − 0.234 × 10+, T -

(6)

where TF is flash point and Tb is normal boiling point both in K. In 1991, another correlation was proposed by Satyanarayana and Kakati for prediction of closed cup flash point of organic compounds from their normal boiling points and specific gravity.12

T = a + b T +

c + d SG T

(7)

where TF is flash point and Tb is normal boiling point both in °C, a = −83.3362, °C; b = 0.5811, dimensionless; c = 0.1118×10-3 °C2 and d = 38.734, °C and SG is the specific gravity, dimensionless.

In 1992, a more complex relationship was proposed by Satyanarayana and Rao13 to predict the flash point from boiling point:


4

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T = a +

c - 68+79 : b 3 4 e T ;1 −

+7 6 : 8 e 9
=> P, 8 @

+

x- γ- P-=> => P-, 8 @

=1

(10)

where x1, x2 are liquid mole fractions; γ1, γ2 are liquid phase activity => => coefficients; P=> , P-=> are vapor pressures at temperature T; P, 8 , P-, 8 are the @ @ vapor pressure at the flash point for components 1 and 2, respectively.

In addition to the above methods, more recently researchers have published some new methods which are mainly applicable to pure hydrocarbons or defined mixtures but not undefined petroleum fuels.16-25 These methods fall into three main categories: empirical correlations, quantitative structure property relationship “QSPR” based methods, and group contribution “GC” methods. In the empirical correlations, properties such as normal boiling point26,27, number of


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carbon and hydrogen atoms28 and flammability limit29 have been used as input parameters. In some other methods, knowledge of chemical composition and molecular structure is required. For example methods based on group contribution technique requires exact structure of a molecule to determine its flash point,30,31 while QSPR method has been proposed for the calculation of flash point of fuels compounds.24 As these methods are not applicable to petroleum mixture of unknown composition we are not considering them in our evaluations. 32 A summary of the methods with their limitations for the estimation of flash point which are used in this study is given in Table 1.

3. DATA COLLECTION For pure hydrocarbons, 64 experimental data were obtained from API-TDB33 data source which include flash point, molecular weight, boiling point, specific gravity and vapor pressure from paraffins, naphthenes and aromatic hydrocarbon families. Generally, properties of these compounds varied from 301 to 651 K for normal boiling point, 70 to 311 g/mol for molecular weight and C5 to C22 for carbon number. Closed cup flash point data for 64 compounds were obtained using the closed cup apparatus by Pensky Martens tester as described in ASTM D 93 test method and it varied from 216 to 466 K. For those samples that vapor pressure at 100 °F was not available, it was calculated through Lee and Kesler method34 as given in the Supporting Information (Part A). For petroleum products, 73 data were obtained from Oil and Gas Journal Data Book35 and Hydrocarbon Processing10 as given in the Supporting Information (Part B). These data are for various petroleum products such as kerosene, diesel, naphtha, gas oil and vacuum distillate.36-40 Flash point data and other properties needed for the estimation of flash point such as temperature on distillation curve at 10% and 50% volume vaporized, specific gravity and compositions are also given in Table B1. Generally, properties of these fractions varied from 265 to 505 K for flash points, 393 to 707 K for ASTM D86 distillation temperatures at 50% vaporized and 0.745 to 0.978 for the specific gravity.

4. EVALUATION OF EXISTING PREDICTIVE METHODS Various flash point methods as presented in Section 2 and Table 1 were evaluated with data for both pure hydrocarbons and petroleum products/fractions. Summary of evaluation results for pure hydrocarbons is given in Table 2 and for petroleum products is given in Table 3. Details of evaluations for these methods are given in Tables C1 and C2 (in the Supporting Information) for pure hydrocarbons and mixtures, respectively. Prugh method (Eq. 4) cannot be applied for calculation of flash point of petroleum fractions as the atomic compositions are not known.


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Therefore, Eq. 4 was not used for flash point estimation of petroleum fractions in these evaluations.

As described earlier, Liaw et al. method is used for mixtures of defined compounds and compositions. This is the reason it was not applied to both pure hydrocarbons or petroleum fractions and it was excluded from Tables 2 and 3 as well as Tables C1 and C2.

Results presented in Tables 2 and 3 show that Eqs. 1 and 2 gave the lowest errors for pure hydrocarbons while Eqs. 3 and 6 gave the highest error and this is mainly attributed to limitation for use of these equations as shown in Table 1. For Eqs 1 and 2 the data used were almost within the limitation range while for other methods some data fell outside of the recommended boiling point range. Another reason for low performance of some of these methods was lack of input data which needed to be estimated.

5. DEVELOPMENT OF A NEW PREDICTIVE METHOD The first attempt was to improve flash point estimation of petroleum mixtures using Liaw method as shown by Eq. 10 for binary mixtures. This method was extended to a petroleum fraction considering a mixture of 3 pseudo-components from paraffins (P), napthenes (N) and aromatics (A) hydrocarbon groups as given below:

Σ

BC DC ECFGH BK DK EKFGH BL DL ELFGH BM DM EMFGH = + + =N FGH FGH FGH FGH EC, I E E E K, I L, I M, I J J J J

(11)

where xi, xp, xN, xA are composition of component i; paraffin; naphthene and aromatic, dimensionless; γi, γp, γN, γA are activity coefficient of component i; => paraffin; naphthene and aromatic, dimensionless; P=> , PO=> , PP, 8 are vapor @ => => => pressure of component i at system temperature, in bar and P, 8@ , PO, 8@ , PQ, 8 and @ => PP, 8@ are vapor pressure of component i at flash point temperature (TF) in bar. Methods of calculation of these properties are given in Appendix A. In Eq. 11 constant F was used instead of unity as was originally used in Eq. 10. Data for flash point of 73 petroleum mixtures given in Table 2 was used to get an optimum value of F in this equation. It was found that even when optimized values of F are used the lowest error one can obtain was 3.6% which is similar to accuracy of Eq. 7 as shown in Table 3. However, Eq. 7 is much simpler than Eq. 11 and requires


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only one input parameter. Considering the complexity of Eq. 11 especially in obtaining input parameters for undefined petroleum mixtures, this approach was considered a failed method and was not pursued further.

Through results presented in Tables 2 and 3, it is seen that the Butler et al. method (Eq. 2) performed well for both pure hydrocarbon and petroleum fractions. In this method two parameters are needed as input parameters: molecular weight and vapor pressure at the flash point temperature. For hydrocarbon systems it is shown that molecular weight is related to boiling point (Tb) and specific gravity (SG) through the following relation:41 MW = a T SG7

(12)

For vapor pressure, we began with simplest method based on Clasius Clapeyron relation as following:1

lnP => = A −

B T

(13)

where A and B are constants and this relation although approximate but it is applicable within narrow temperature range (ie between flash point and boiling point). Constant B can be calculated from the heat of vaporization (∆Hvap) as given below:

B=

∆H R

(14)

The most approximate and simple rule to calculate the heat of vaporization was from Trouton’s rule at normal boiling point HV = 88 Tb. Constant A in Eq. 13 can be determined from vapor pressure at boiling point which is the same as atmospheric pressure Pa. Substituting these values for A and B, Eq. 13 reduces to the following simple relation for vapor pressure in terms of boiling point and atmospheric pressure.


8

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P = P exp X10.58 61 −

T :Y T

(15)

Substituting Eqs 12 and 15 into Eq. 2, gives:

a T SG7 P exp X10.58 61 − Now let Q =

.[\ O]

T :Y = 1.096 T

(16)

and C1=10.58, the above equation can be expressed in the

following form:

T b c lnQ = lnT + ln SG + 1 − T C C C

(17)

Examination of data for single carbon number hydrocarbon groups showed that the right hand side of the above equation was nearly constant. This analysis showed that flash point and boiling point are possibly related through the following simple relation. T = α T

(18)

This relation was applied for pure hydrocarbons and petroleum fractions, constant (α) was determined as 0.71 (0.714 from data analysis) for pure hydrocarbons and of 0.69 for petroleum fractions as shown in Fig. 1. In Eq. 18 both TF and Tb are in Kelvin. Results showed errors of 1.7% for pure hydrocarbons and 2.8% for petroleum fractions in which data are given in the Supporting Information. This evaluation of Eq. 18 should be compared with the results presented in Tables 2 and 3 for previously developed methods. The lowest error for pure hydrocarbons as shown in Table 2 is 1.6% for Eq. 2 and for petroleum fractions the lowest error as shown in Table 3 is 3.7% for Eq. 7.

A single value for the constant (α) was found to be 0.7 for both pure hydrocarbons and petroleum fractions. It is a simple relation and easy to remember, however for accurate prediction one should use specific values of 0.71


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for pure hydrocarbons and 0.69 for petroleum fractions or products. Generally this was expected that (α) for petroleum fractions is less than its value for pure hydrocarbons as for mixtures the lighter hydrocarbons have greater impact on the flash point of mixture as discussed in the previous publications.1,7 This value of α gave errors of 2.6% for pure hydrocarbons and 3.1% for petroleum fractions. Therefore, the ratio of TF/Tb is about 0.7 (both temperatures are in K) for both pure hydrocarbons and their mixtures for a quick estimate. For petroleum fractions 50% ASTM D86 temperature should be used for Tb. This method is far simpler than other methods presented in Table 1.

Further evaluation of Eq. 18 is shown in Figs. 2, 3 and 4. In Fig. 2, Eq. 18 with 9 other methods (Eqs. 1-9) are compared and evaluated with data for nalkycyclohexanes. Predicted versus experimental values of flash point for pure hydrocarbons are also shown in Fig. 3. Similar evaluation of Eq. 18 for petroleum mixtures is demonstrated in Fig. 4. The group contribution methods (GCM) developed for estimation of flash point of pure compounds were not included in our evaluations as they are not applicable to undefined petroleum mixtures. However, one of the latest and simplest GC methods has been used to compare with Eq. 18 and it is in the following form:30 T = 12.14 + 0.73 T + ∑niαi

(19)

where ni and ϕi are the number of presence and the amount of contribution of functional group i, respectively.30 Eq. 19 was used to evaluate flash points of nalkanes from C5 to C25 and was compared with Eq. 18 proposed in this work. Average absolute deviation for Eq. 18 was 1.39 and for Eq. 19 was 1.63%, respectively, and this evaluation is also presented in Fig. C1 in the Supporting Information.

Additional evaluation was made based on data not given in Table A1. Flash point data for five petroleum products from various sources was collected and is given in Table A2 with known specific gravity. Estimated flash point data from all previous methods and Eq. 18 are given in Table 6 and corresponding errors are given in Table C4 of the Supporting Information. Results presented for both pure hydrocarbons (Table 2) and petroleum products (Tables 3 and C4) indicate that the simple relation proposed in this paper (Eq. 18) is quite comparable or better than existing methods and cover wider boiling range for the petroleum products. The proposed method is much simpler than the existing methods and suggests that the ratio of flash point to boiling point is a constant. The main purpose of this work was to predict flash point petroleum mixtures when minimum information is


10

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available for a mixture. In this work a very simple method has been proposed that from only mid-boiling point data, flash point of a hydrocarbon mixture or a petroleum product can be estimated with accuracy better than the existing methods reported in open literature. SUPPORTING INFORMATION There is a Supporting Information attached to this paper which has 3 parts as following: Part A- Methods and equations for estimation of input parameters, Part B- Data on flash points of petroleum fractions as given in Tables B1 and B2, Part C- Detailed estimated values of flash points from various methods as given in Tables C1 and C2. Evaluation of methods with independent data as given in Tables C3 and C4 as well as Fig. C1.

TABLES

Table 1. Classification and limitation of estimation methods for the flash point temperature studied in this work Method

Chemical Class

Input parameters

Limitation

Butler et al. (Eq. 1)

Middle Distillates

Tb

366.5 ≤ Tb ≤ 644.3 K


Middle Distillates

Pvap, MW

366.5 ≤ Tb ≤ 644.3 K

Walsh-Mortimer (Eq. 3)

Hydrocarbons

Pvap

Prugh (Eq. 4)

Organic compounds

Tb, Cn, Hn

144.3 ≤ TF ≤ 477.6 K

Riazi-Daubert (Eq. 5)

Hydrocarbons, Fractions

T10% or Tb

338.7 ≤ Tb ≤ 866.5 K

Patil (Eq. 6)

Organic compounds

Tb

Satyanarayana-Kakati (Eq. 7)

Organic compounds

Tb, SG

Satyanarayana-Rao (Eq. 8)

Organic compounds

Tb

Hshieh (Eq. 9)

Organic compounds

Tb

Liaw et al. (Eq. 10)

Organic Mixture

x,γ, Psat, E IFGH J

Not available

260 ≤ TF ≤ 500 K 293.2 ≤ Tb ≤ 613.2 K Not available 263.2 ≤ Tb ≤ 648.2 K Not available

Tb: normal boiling point temperature; T10%: distillation temperature at 10% vaporized; Cn: carbon number; Hn: hydrogen number; SG: specific gravity; Pvap: vapor pressure; MW: molecular weight. x: liquid mole fraction; γ: liquid phase activity coefficient; Psat: vapor pressure at temperature T; E IFGH : vapor pressure at flash point. J


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Table 2. Evaluating flash point estimation methods for pure hydrocarbons Absolute Deviation

%Absolute Deviation

Method AAD, K

MAD, K

%AAD, K

%MAD, K


5.9

24.8

1.7

6.5


5.4

29.1

1.6

7.6


19.1

78.1

4.9

17.0

Prugh (Eqn. 4)

8.8

35.8

2.4

8.2


10.8

42.2

3.0

9.1

Patil (Eq. 6)

15.1

30.4

4.9

12.2


10.5

34.0

3.1

7.8


9.2

27.6

2.8

12.8

Hshieh (Eq. 9)

10.5

33.3

3.4

9.4

Table 3. Evaluating flash point estimation methods for petroleum fractions Absolute Deviation

%Absolute Deviation

Method AAD, K

MAD, K

%AAD, K

%MAD, K


15.0

51.3

4.2

13.4


16.4

58.5

4.5

14.1


42.1

146.1

11.1

34.6


16.9

69.7

4.7

13.8

Patil (Eq. 6)

23.6

53.9

6.8

17.4


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13.3

38.0

3.7

13.4


19.9

68.1

5.7

20.2

Hshieh (Eq. 9)

22.0

65.8

6.2

15.7

FIGURES

500

450

Experimental Flash Point, K

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400

350

300

250

200 250

350

450

550

650

750

Experimental Boiling Point, K

Figure 1. Evaluation of Eq. (18) for pure hydrocarbons


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340

320

Flash Point, K

300

280

260

240 350

370

390

410

430

450

Boiling Point, K

Figure 2. Evaluation of various methods for prediction of flash point of n-alkylcyclohexanes:

○ Data;

Butler et al. (Eq. 1);

Butler et al. (Eq. 2);

Walsh-Mortimer (Eq. 3);

Prugh (Eq. 4);

Riazi Daubert (Eq.5);

Patil (Eq. 6);

Sat. Kakati (Eq. 7); Hshieh (Eq. 9);

Sat. Rao (Eq. 8); New Method (TF=0.7Tb)

500

450

400

Calculated Flash Point, K

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350

300

250

200 200

250

300

350

400

450

500


Figure 3. Parity chart for the prediction of flash point from Eq. (18) for pure hydrocarbons


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500

450

Calculated Flash Point, K

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400

350

300

250 250

300

350

400

450

500


Figure 4. Parity chart for the prediction of flash point from Eq. (18) for petroleum fractions

ACKNOWLEDGEMENTS

This paper has been prepared based on the MSc thesis in chemical engineering (Kuwait University) by Sara S. Alqaheem. This paper was also presented at the Annual Meeting of AIChE, November 8-13, 2015, Salt Lake City, UT, USA.

REFERENCES (1) Riazi, M. R. Characterization and Properties of Petroleum Fractions. MNL50: West Conshohocken, PA, 2005. www.astm.org/DIGITAL_LIBRARY/MNL/SOURCE_PAGES/MNL50.htm

(2) Riazi, M. R.; Eser, S.; Agrawal, S. S.; Pena Diez, J. L. Petroleum refining and natural gas processing. MNL58: West Conshohocken, PA, 2013. www.astm.org/DIGITAL_LIBRARY/MNL/SOURCE_PAGES/MNL58.htm

(3) Riazi, M. R. Exploration and production of petroleum and natural gas; ISBN: 978-08031-7068-1: U.S.A., 2016.


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www.astm.org/DIGITAL_LIBRARY/MNL/SOURCE_PAGES/MNL73.htm

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Flash Points of Hydrocarbons and Petroleum Products: Prediction and

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