PRACTICAL DATA CORRELATION OF FLASHPOINTS OF BINARY MIXTURES BY A RECIPROCAL FUNCTION: THE CONCEPT AND NUMERICAL EXAMPLES

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HERMAL SCIENCE, Year 0, Vol. 5, No. 3, pp. 905-90 905 Open forum PRACICAL DAA CORRELAION OF FLASHPOINS OF BINARY MIXURES BY A RECIPROCAL FUNCION: HE CONCEP AND NUMERICAL EXAMPLES by Mariana HRISOVA a, Dimitar DAMGALIEV b, and Jordan HRISOV c * a Department of General Chemical echnology, University of Chemical echnology and Metallurgy, Sofia, Bulgaria b Department of Automation, University of Chemical echnology and Metallurgy, Sofia, Bulgaria c Department of Chemical Engineering, University of Chemical echnology and Metallurgy, Sofia, Bulgaria Original scientific paper UDC: 536.468:57.538 DOI: 0.98/SCI0608067H Introduction Simple data correlation of flashpoint data of binary mixture has been developed on the basis of rational reciprocal function. he new approximation requires has only two coefficients and needs the flashpoint temperature of the pure flammable component to be known. he approximation has been tested by literature data concerning aqueous-alcohol solution and compared to calculations performed by several thermodynamic models predicting flashpoint temperatures. he suggested approximation provides accuracy comparable and to some extent better than that of the thermodynamic methods. Keywords: flashpoint, binary mixtures, reciprocal function, data approximation he flash points () of flammable or combustible liquids are data required to establish the fire and explosion hazards and classifications of materials according to the classes defined in each particular regulation [, ]. his, therefore, requires knowledge related to both the principles of combustion and the fluid phase equilibria. he flash point is defined as the lowest temperature (corrected to 0.3 kpa) at which the vapors of a specimen ignite, under specified conditions of a test [], by application of an external ignition source, and therefore the lower explosion limit exceeds the flash point [3]. he flash points are almost constant characteristics of materials tested but the published values vary because they strongly depend on the design of the testing device. Usually, the closed-cup method [4] is used because the results tend to be on the safe side, while the open-cup measurements [4] are not reliable, to some extent, due to a systematic errors caused by volatile compounds escape from the measuring equipment. A particular flash point can therefore only be defined in terms of a particular standardized test method. *ncorresponding author; e-mail: jordan.hristov@mail.bg

906 HERMAL SCIENCE, Year 0, Vol. 5, No. 3, pp. 905-90 he existing estimation methods, especially for closed cup flash points [5-9] are based on iterative calculations and use combinations of (a) Dalton s and Raoult s laws for ideal solutions [0]; (b) corrected Raoult s law for non-ideal solutions [0], the Antoine equation [], and the Le Chatelier s rule []. Many data published in the literature are based on experiments, thus incorporating either experimental or systematic errors. A statistical analysis; therefore, providing handy relationships is highly required. he present communication addresses handy approximation of binary aqueous mixtures by a reasonable relationship allowing predicting easily when only the concentration of the flammable component (x ) is known. We address water-alcohol mixtures (data taken from [3]) as good examples with non-ideal behaviours, allowing to calculate by different thermodynamic models and iterative calculations (by Matlab), as parallel prediction procedures [4]. Approximations developed Commonly, 3 rd order polynomial correlations for is used [3] to fit particular sets of experimental data, i. e. 3 b0 b x b x b3 x () where x = x, the molar fraction of the flammable component (FC) of the water(x )-FC(x ) mixture. his type of relationships has 4 coefficients inherently affected by the uncertainty in the experiments and the regression procedure. he present works conceive an a approximating relationship from the family of the rational functions, the so-called reciprocal function, requiring an initial normalization of the experimental data by of the pure flammable component is conceived, namely: y, y () a bx x.0 In (), we have a + b because at x, we have y. Numerical experiments Data correlations by equations developed (tab. ) for some water-based binary mixtures on the basis of () and () were performed together with iterative calculations [4] based on thermodynamic models. he outcomes concerning some sample mixtures [4] are summarized in tabs. -4. he data summarized indicate almost equal level off approximation (based on the absolute point-wise errors) of both the empirical approximations and the prediction of the thermodynamic models. he conceived reciprocal function fits the experimental data better than the 3 rd polynomial expressions. Errors comparable to those provided by the polynomial relationships were observed with water-iso-propanol mixtures (tab. 5) only. Some special features and advantages of the suggested approximation functions are commented next. Comments he equations developed have only one goal: to fit the experimental data with a minimum error of approximations. In general, both type of equations used lead to almost

HERMAL SCIENCE, Year 0, Vol. 5, No. 3, pp. 905-90 907 equal errors of approximations within the range 0. x.0. he reciprocal approximation is more practical because only two coefficients a and b, as well as, the of the pure flammable component, have to be known. he polynomial approximation needs 4 coefficients but is not needed for the calculations. However, the (x=) is a useful initial datum allowing to normalize the experimental data as y = /(x=.0) and control the adequacy of approximation taking into account that at x, we have y and a + b. able. Flash-point approximations developed Binary mixture Polynomial approximation Reciprocal approximation Water-methanol (x) Water-ethanol (x) Water-propanol (x) Water-iso-propanol (x) = 56.7 48x + 87x 86.x 3 R = 0.995; SSE = 5.5 3 40. 86.x x 63x R 0.983; SSE 5.54 3 3.5 5.9 8.7x 5.36x R 0.983; SSE. ( x=.0) R ( x.0) R (0.48 0.765 x) 0.995; 0.00576 ( x.0) R (0.345 0.608 x) 0.964; 0.00856 (0.705 0.90 x) 0.976; 0.0004 3 6. 34.0 x 48. x 7.6 x (0.56+0.43 x) R 0.994; SSE 0.53 ( x=.0) R =0.967; χ =0.0008 Тable. Mixture flash points of water()-methanol() x Exp. data hermodynamic-based model predictions Approximations (present work).0 0.0 9. 0.8 0.93 0.93 D R 0.9 0.6.7..7..7..8..9.3.93.33 0.8 3.7 3.6 0. 3.6 0. 3.4 0.3 3.9 0. 3.7 0.0 3.3 0.56 0.7 5.6 5.5 0. 5.5 0. 5.3 0.3 6. 0.6 5. 0.5 4.60 0.99 0.6 6.3 7.6.3 7.6.3 7. 0.9 9.0.7 6.5 0. 6.44 0.4 0.5 9. 9.9 0.7 9.9 0.7 9.3 0..4 3. 8.6 0.6 8.8 0.38 0.4.3.6 0.3.6 0.3.8 0.5 6.7 4.4.9 0.4.98 0.3 0.3 6.7 6. 0.6 6.3 0.4 5..6 3.4 5.7 6.8 0. 6.43 0.6 0. 3.6 3.6.0 3.8. 30..4 40.9 8.3 33.9.3 33.4 0.54 0. 44.5 4.8.7 4.9.6 40.8 3.7 56.7. 43.7 0.8 44.4 0.07

908 HERMAL SCIENCE, Year 0, Vol. 5, No. 3, pp. 905-90 able 3. Mixture flash points of water()-ethanol() x Exp. data hermodynamic-based model predictions Approximations (present work).0 3.0.5-0.5 3.6 0.6 0.9 4.6 4.8 0. 4.8 0. 4.5 0. 4.7 0. 5. 0.5 4.54 0.05 0.8 6.3 6.7 0.4 6.5 0. 5.8 0.5 6.6 0.3 6.8 0.5 5.60 0.69 0.7 7.5 8.6. 8.3 0.8 7. 0.4 8.7. 7.8 0.3 6.83 0.66 0.6 9.5 0.4 0.9 0.0 0.5 8.3..3.8 8.7 0.8 8.7. 0.5 0.4.9.5.7.3 9.4.0 4.4 4.0 9.7 0.7 9.98 0.4 0.4 0.8 3.4.6 3.4.6 0.6 0. 8.3 7.5. 0.4.05.5 0.3 4.0 5.0.0 5.3.3.0.0 33.5 9.5 3.6 0.4 4.59 0.59 0. 5.8 7.6.8 8..3 4..7 4. 5.4 7.3.5 7.79.99 0. 33.6 34.5 0.9 34.6.0 9. 4.5 55.5.9 3.8 0.8 3.95.64 D R Тable 4. Mixture flash point of water()-propanol () Exp. data hermodynamic-based model predictions Approximations (present work) x.0 3.0.7 0.3 3.08 0.08 0.9 3.4 4.7.3 4.5. 4.3 0.9 4.6. 3.6 0. 3.77 0.37 0.8 3.9 6.6.7 6. 5.3.4 6.3.6 4.5 0.6 4.5 0.6 0.7 6 8.5.5 7,4.4 6. 0. 8.4.4 5.4 0.6 5.9 0.70 0.6 6.3 30 3.7 8.8.5 6.7 0.4 30.8 4.5 6.4 0. 6.3 0.6 0.5 7. 30.8 3.6 30.8 7.3 0. 33.7 6.5 7.3 0. 7.0 0.7 0.4 8. 30.9.8 30.8.7 7.8 0.3 37.4 9.3 8. 0. 7.97 0. 0.3 9.6 30 0.4 3..5 8.3.3 4.3.7 9. 0.5 9.00 0.59 0. 9.7 8.8 0.9 30.8. 8.8 0.9 49.6 9.9 30.0 0.3 30.0 0.40 0. 3 9.6.4 3 0 30 63. 3. 3.0 0.0 3.9 0.9 D R Тable 5. Mixture flash point of water()-iso-propanol() Exp. data hermodynamic-based model predictions Approximations (present work) x appr.0 3.0.8 0. 4.89.89 0.9 4.3 4.6 0.3 4.5 0. 4.4 0. 4.6 0.3 4.5 0. 5.5.8 0.8 5.6 6.3 0.7 6 0.4 5.5 0. 6.4 0.8 5.7 0. 6.33 0.73 0.7 6.5 7.9.4 7.4 0.9 6.5 0 8.4.9 6.5 0.0 7.6 0.66 0.6 7.3 9.3 8.8.5 7.4 0. 0.9 3.6 7. 0. 8.08 0.78 0.5 8 0.. 0 8. 0. 3.8 5.8 7.8 0. 9.0.0 0.4 8.8 0.5.7. 8.9 0. 7.5 8.7 8.5 0.3 0.4.44 0.3 9.3 0.5..8.5 9.6 0.3 3.4 3. 9.6 0.3.53.3 0. 0.7 0.4 0.3.6.9 0.5 0. 39.7 9. 0.4.99.9 0. 3.5 3 0.5 5..7.4. 53. 9.6 3. 0.3 4.67.7 D R

HERMAL SCIENCE, Year 0, Vol. 5, No. 3, pp. 905-90 909 Nomenclature a dimensionless coefficient in eq. b dimensionless coefficient in eq. b0, b,... dimensionless coefficients in eq. R residual variance, [ ] flash point temperature, ( x ) flash point temperature of the pure flammable component, x mol fraction of a given component of the mixture, [ ] x mol fraction of the water, [ ] x mol fraction of the flammable component, [ ] y dimensionless flash point defined by eq. (= /(x=.0) ) Greek symbols IE ME error in data correlation, (= predicted experimental ), error of the method based on the Raoult s law (ideal solutions), error between the experimental data and those predicted by the Margules method, poly error of the polynomial approximation, R error of the reciprocal approximation, vle error of the van Laar method, WE error of the Wilson method, the Pearson s Chi-square, [ ] Subscripts Abbreviations Flash point exp experimental flash point I ideal (Raoult s law) M Margules method P polynomial R reciprocal SSE sum of squared errors, [ ] vl van Laar method W Wilson method References [] ***, CCPS/AIChE, Guidelines for Engineering Design for Process Safety. American Institute of Chemical Engineers, New York, USA, 993 [] ***, Regulation (EC) No. 907/006 of the European Parliament and of the Council Concerning the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH), 006 [3] Lees, F. P., Loss Prevention in the Process Industries, nd ed., Butterworth-Heinemann, Oxford, UK, Vol., 996 [4] Lance, R. C., Barnard, A. J., Hooyman, J. E., Measurements of Flash Points: Apparatus, Methodology, Applications, J.Haz.Mater., 3 (979),, pp. 07-9 [5] Gmehling, J., Rasmussen, P., Flash Points of Flammable Liquid Mixtures using UNIFAC, Ind.Eng.Chem.Fund, (98), 3, pp. 86-88 [6] McGovern, J. L., A Method for Estimating the Flash Points of Coating Mixtures of Oxygenated and Hydrocarbon Solvents and Petroleum Distillates Part II, J. Coats echnol, 64 (99), 80, pp. 39-44 [7] Liaw, H. J., et al., A Mathematical Model for Predicting the Flash Point of Binary Solutions, J Loss Prev Proc Ind, 5 (00), 6, pp. 49-438 [8] Catoire, L., Paulmier, S., Naudet, V., Estimation of Closed Cup Flash Points of Combustible Solvent Blends, J Phys Chem Ref Data, 35 (006), pp. 9-4 [9] Vidal, M., Rogers, W. J., Mannan, M. S., Prediction of Minimum Flash Point Behaviour for Binary Mixtures, Process Safety and Environmental Protection, 84 (006), B, pp. -9 [0] Sandler, S., Chemical and Engineering hermodynamics, John Wiley & Sons, New York, USA, 977 [] Boublik,., Fried, V., Hala, E., he Vapor Pressures of Pure Substances, Elsevier, Amsterdam, he Netherlands, 973 [] Le Chatelier, H., Estimation of Firedamp by Flammability Limits. Ann. Mines, 9 (89), 8, pp. 388-395 [3] Liaw, H. J., Chiu, Y. Y., he Prediction of the Flash Point for Binary Aqueous-Organic Solutions, J.Haz.Mater, 0 (003),, pp. 83-06

90 HERMAL SCIENCE, Year 0, Vol. 5, No. 3, pp. 905-90 [4] Hristova, M., Damgaliev, D., Popova, D., Estimation of Water-Alcohol Mixture Flash Point, J. UCM, 45 (00),, pp. 9-4 [5] Reid, R. C., Prausnitz, J. M., Poling, B. E., he Properties of Gases and Liquids, McGraw-Hill, New York, USA, 987 Paper submitted: November 9, 00 Paper revised: March, 0 Paper accepted: March 4, 0