Mathematical description of the kraft recovery boiler furnace

European Symposium on Computer Aided Process Engineering - 13 A. Kraslawski and I. Turunen (Editors) © 2003 Elsevier Science B.V. All rights reserved.

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Mathematical Description of the Kraft Recovery Boiler Furnace A. O. S. Costa, E. C. Biscaia Jr. and E. L. Lima* Programa de Engenharia Quimica - COPPE/UFRJ Cidade Universitaria - CP: 68502. CEP 21945-970. Rio de Janeiro, Brasil. *[email protected] .br

Abstract It is proposed a new (hybrid) approach for the mathematical description of the black liquor burning process in an industrial recovery boiler furnace. The system is divided into four different regions and the concentration of each chemical substance in each region is calculated by direct minimisation of the corresponding Gibbs free energy. The particulate formation is separately described through a neural network trained with industrial data. The resulting hybrid model satisfactorily reproduces black liquor burning data obtained from literature and industrial sources.

1. Introduction A stationary mathematical model that describes Kraft recovery boilers is under development at the Programa de Engenharia Quimica of COPPE/UFRJ. This study has the technical support of one of the biggest Brazilian pulp and paper companies (Klabin Parana Papeis - KPP). As part of this research project, a mathematical model of the black liquor burning in the furnace of the boiler has been developed and constitutes the main purpose of the present contribution. 1.1. Black liquor burning Grace (1992) makes a detailed description of the different stages involved in the black liquor burning process: • Drying stage: the particle loses its residual humidity; • Pyrolysis stage: the particle increases its volume due the gas generation; (the generated gases are: TRS (Total Reduced Sulphur: CH3SH, CH3SCH3, CH3S2CH3), SO2, CO2, CO, CH4, H2O); • Char burning stage: the particle volume reduces with corresponding density increase, then the particle arrives at the furnace bottom; • Oxidation and reduction of the inorganic salts stages: Na2S reacts exothermically with the oxygen producing Na2S04. Na2S is the inorganic salt that should be recovered in the furnace due its importance as an active agent of the wood digester process. The relation between the recuperated sulphur mass as Na2S and the total sulphur mass present in the smelt is called reduction efficiency. Although the smelt oxidation causes a decrease of the reduction efficiency, the energy produced during this reaction facilitates the fusion of the inorganic salts forming the smelt. Besides, this energy favours the endothermic reduction of the Na2S04. This component reacts with carbon forming again Na2S.

1008 A particulate material composed by unburned liquor particles and inorganic salts (chemistry dust) is still formed during the black liquor burning. Part of this material is carried out to other parts of the recovery boiler.

2. Methodology The characteristic reactions of the black liquor burning, except the ones involved in the particulate formation, are described by a technique based on the minimisation of Gibbs free energy. For this purpose, the KPP furnace has been divided in four regions (Figure 1). In each region, different stages of the process are described: • Drying region: drying of the particle residual humidity; • Region 1: black liquor pyrolysis and generation of combustion gases; • Region 2: particle residual carbon combustion and smelt formation; • Region 3: combustion of reduced substances coming from the furnace bottom. The burning reactions of the black liquor have been considered only in regions 1, 2 and 3. Thus, the concentration of the chemical species has been determined in each of these regions. The numbers of phases and chemical species in each region have been chosen based on information reported in the literature. A Sequential Quadratic Programming (SQP) method has then been used to solve the minimisation problem.

Region 3

Tertiary air Oivii"

Black liquor feed

Tertiary air Black liquor feed

Drying Region

Region 1

Secondary air Primary air

Region 2

Secondary air Primary air

^4E^

Smelt Smelt Figure 1: Regions considered in the mathematical description of the furnace. Due to the complexity of the particle formation phenomenon, Jokiniemi et al. (1996), this process is described separately through an empirical model using industrial data, supplied by KPP. Preliminary tests have shown that linear models cannot describe the relation between the variables evolved in this process at the same time the chemical mechanisms of the particle formation is not completely known. So a neural network has been developed to describe the particle formation phenomenon.

3. Results 3.1. Minimisation of Gibbs free energy The results presented in the present contribution have been obtained adopting constant values for the black liquor feed (29.57kg/s), the black liquor solids concentration (84%),

1009 the primary air feed mass flow (38.52kg/s), the secondary air feed mass flow (34.85kg/s) and the tertiary air feed mass flow (18.34kg/s). Information suppHed by KPP report that in the same operation conditions the reduction efficiency observed is 96.88% and the TRS emission is 0.82ppm. The general considerations adopted during Gibbs free energy minimisation of regions 1, 2, and 3 are: the black liquor is composed by C, H, O, Na and S; the regions 1, 2 and 3 have, respectively, constant mean temperatures Ti, T2 and T3; the furnace operates at latm; all present phases are considered as ideal; the black liquor particles arrive dried at region 2; the feed to region 3 is composed by the particle residual humidity, the tertiary air and the gaseous phases coming from regions 1 and 2; region 1 is formed by 2 phases (solid and gaseous); region 3 is formed by only one gaseous phase; the nitrogen is inert in the furnace. Moreover, it has been considered that all the reduction and oxidation reactions, in region 2, occur in the solid phase. Thus, after reaching the chemical equilibrium, the inorganic species only melt to form the smelt. Consequently, during the minimisation of the Gibbs free energy in region 2, only two phases have been considered: one solid and one gaseous. The preliminary results indicate that part of the primary and secondary air feed goes directly to region 1 without reacting in region 2. Thus, it is adopted a parameter (Pd) to simulate this behaviour. Additional tests were made to obtain the correct value of Pd for the simulated operation condition. The obtained results show that 40% of the primary and secondary air feed reacts in region 2 (Pd = 40%). The Gibbs free energies of regions 1 and 2 were minimised and the corresponding results are presented in Tables 1 and 2. In this test, different values of Ti and the mean temperature supplied by KPP for region 2 (T2 = 1080°C) were adopted. Table 1: The chemical composition of region 1. T,CQ

Testl 200

Test 2 300

substances C(s) NazCOaCs) Na2S04(s) Na2S(s) NaOH(s) 02(g) H2(g) C02(g) CO(g) H20(g) S02(g) CH3SH(g) CH3SCH3(g) CH3S2CH3(g) CH4(g) N2(g) Gases TRS (ppm) SO2 concentration (ppm)

80.06 13.15 6.79 0 0 0 0.29 13.89 4.73 13.48 0 0 0 0 2.11 65.50 0.29 2.07

78.98 13.89 7.04 0.09 0 0 0.66 15.08 3.30 12.48 0 0 0 0 2.49 65.99 69.15 5.38

Test 3 Test 4 Test 5 400 500 600 Region 1: molar composition (%) 74.84 71.02 76.51 15.55 16.59 19.08 0.01 1.06 0 6.88 8.55 9.85 0.01 0 0.05 0 0 0 2.00 4.59 8.14 15.10 15.81 14.83 3.59 3.19 4.54 12.00 10.19 7.67 0 0 0 0.01 0 0 0 0 0 0 0 0 1.97 1.50 0.88 65.34 64.72 63.94 7.24 148.01 0.08 1.37 3.27 11.39

Test 6 700 58.72 27.13 0 14.02 0.13 2.18 11.25 9.99 9.27 5.05 0 0 0 0 0.35 61.91 0.01 0

Lisa (1997) affirms that the TRS formation begins when the black liquor particle achieves 200°C and ends at 600°C. This information has been reproduced by the results present in Table 1. The carbon consumption of the solid phase in region 1 increases with the increase of T]. Consequently, particles leave this region with a low concentration of this element. Due

1010 this reason, the oxygen is used to oxidise the inorganic salts in region 2. Therefore, the reduction efficiency decreases with an increase of Ti. Table 2: The chemical composition of region 2. Test 1 200

Test 2 300

02(g) H2(g) C02(g) CO(g) H20(g) S02(g) CH4(g) N2(g)

0.03 65.25 0.67 33.19 0.86 0 0.39 19.12 8.45 1.86 0 0 70.18

0.02 65.34 3.14 30.62 0.88 0 0.28 20.31 5.95 2.01 0 0 71.45

0.03 65.40 1.08 32.54 0.95 0 0.37 16.98 6.62 1.99 0 0 74.04

Reduction Efficiency (%)

98.03

90.71

96.80

TiCC) Substances C(s) Na2C03(s) Na2S04(s) * Na2S(s) NaOH(s)

Tests 400

Test 4 500

Test 5 600

Test 6 700

0.02 65.18 3.77 30.07 0.96 0 0.28 17.19 4.82 2.13 0 0 75.58

0 65.12 20.85 12.97 1.06 0 0.16 16.46 2.43 2.35 0 0 78.60

0 64.88 33.80 0 1.32 4.76 0 11.36 0 2.59 0 0 81.29

88.86

38.35

0

Region 2: molar composition (%)

The obtained smelt concentration (smelted solid phase of region 2) is usually composed by 33% of Na2S and 66% of Na2C03, reproducing the smelt behaviour reported by Grace (2001) and Macek (1999). The real reduction efficiency has been reproduced when Ti is 400°C. In another test, the Gibbs free energies of regions 1, 2 and 3 were minimised considering different values of T3. The chemical composition of regions 1 and 2 are presented in Table 1, test 3 and Table 2, test 3. Table 3 shows the results obtained for region 3. Table 3: The chemical composition of region 3. T3CC)

Testl 200

Test 2 300

0 1.72 15.51 0.13 18.48 0 0.01 0 0 0.48 63.67 117.47 0.17

0 2.82 15.03 0.94 18.14 0.01 0 0 0 0 63.06 5.25 149.80

Test 4 500

Test 5 600

Test 6 700

0 2.15 14.34 1.62 18.82 0.01 0 0 0 0 63.06 0 156.78

0 1.66 13.85 2.11 19.31 0.01 0 0 0 0 63.06 0 156.77

Region 3: molar composition (%)

Substances 02(g) H2(g) C02(g) CO(g) H20(g) S02(g) CHsSHCg) CHsSCHsCg) CH3S2CH3(g) CH4(g) N2(g) Gases TRS (ppm) SO2 concentration (ppm)

Test 3 400 0 2.65 14.84 1.12 18.32 0.01 0 0 0 0 63.06 0.73 155.83

0 2.47 14.66 1.30 18.49 0.01 0 0 0 0 63.07 0.08 156.67

Lisa (1997) affirms that the tertiary air oxidises the TRS gases coming from the furnace bottom. This behaviour is reproduced by the results presented in Table 3. During this study, it was observed that the reduction efficiency is not strongly affected through modifications in Ti or T3. Moreover, assuming values for Pd between 30 and 40%, it has been possible to predict the real reduction efficiency of KPP for different operational conditions.

1011 However, small modifications in Ti or T3 affect significantly the calculated concentration of TRS gases. This behaviour is due to the precision of the optimisation problem resolution, since TRS gases are present in a very small amount (ppm) compared to other chemical species. Thus, the minimisation of the Gibbs free energy technique is not robust enough to predict the TRS gases emission. 3.2. Empirical description of particulate formation Different feedforward neural networks with three layers have been tested to describe the particulate formation in the KPP furnace. A linear activation function has been used in the first layer and tan-sigmoid activation functions were used in the hidden and output layers. Training has been accomplished through 1000 epochs using a backpropagation algorithm. The data have been carefully pre-treated eliminating all data that presented significant measurement errors. A total of 3705 data sets have been used for the training procedure and validation has been based on another 676 data sets, chosen at random. The evaluation of each neural network prediction efficiency has been accomplished using the sum of the squared errors of the validation and training procedures and also by graphic analysis. The best neural network obtained has 9 inputs (temperature, pressure and rate of the furnace black liquor feed; pressure and rate of the primary air feed; pressure, temperature and rate of secondary air feed and tertiary air feed rate) and 12 neurons in the hidden layer. The neural network output (Pf) represents the number of particles per minute (apm) passing through a specific region of the furnace. Figures 2 and 3 show the training and validation results. 900800

o

Epart predicted == Epart real Epart real = Epart real

y^

700 600 500 400 300

J^^^°^

o

2001000570

575

580

585

590

training tests

595

600

100 200 300 400 500 600 700 800 900

Pf real (apm)

Figure 2a: Behaviour of the real and predicted Figure 2b: Relation between the predicted and data to some training tests. real values to all training tests. Figure 2: Behaviour of the best neural network (training tests). The prediction efficiency of the best neural network is not uniform. The results presented in Figure 3 show that for Pf values larger than 300apm, the neuronal network presents smaller prediction efficiency. This behaviour can be associate to the small amount of training data for Pf > 300apm. However, the neural network presented in Figures 2 and 3 can satisfactorily describe the data tendency. Thus, this model has been incorporated to the mathematical model described in item 3.1.

1012

900 800-1

o Epart predicted = Epart real — Epart real = Epart real

700 600^ 500 400 300 200 100 0 225

230

235

240

245

validation tests

250 255

100 200 300 400 500 600 700 800 900 Pf real (apm)

Figure 3a: Behaviour of the real and predicted Figure 3b: Relation between the predicted and data to some validation tests. real values to all validation tests. Figure 3: Behaviour of the best neural network (validation tests).

4. Conclusion A methodology based on the minimisation of Gibbs free energy has been successfully adopted to describe the chemical composition of an industrial black liquor recovery boiler smelt. Moreover, the chemical composition reported in the literature from other industrial sources could also be satisfactorily reproduced using this technique. Industrial data, supplied by KPP, were used to build an empirical model that describes the particulate formation in the furnace. The feedforward neural network chosen to describe the phenomenon has three layers, 9 inputs and 12 neurons in the hidden layer. This model predicts the amount of particles formed in the furnace and carried to another part of the recovery boiler. A low computational cost is required to solve the resulting hybrid model (thermodynamic model plus neural network). Thus, this model can be used to analyse the effect of different operation conditions on the black liquor burning.

5. References Grace, T.M., 1992, Chemical Recovery Process Chemistry, Chemical Recovery in The Alkaline Pulping Processes, Eds. R. P. Green and G. Hough, TAPPI Press, Atlanta. Grace. T.M., 2001, A Review of Char Bed Combustion, International Chemical Recovery, Conference, 65, Canada. Jokiniemi, J.K., Pyykonen, J., Mikkanen, P. and Kauppinen, E.L., 1996, TAPPI Journal, 171.79. Lisa, K., 1997, Recovery Boiler Air Emissions, chapter 8: Kraft Recovery Boilers, Eds. T. N. Adams, TAPPI Press, Atlanta. Macek, A., 1999, Process in Energy and Combustion Science, 275,25.

6. Acknowledgements The authors acknowledge the financial support provided by CNPq - Conselho Nacional de Desenvolvimento Cientifico e Tecnologico - as well as the technical support from Klabin Parana Papeis (KPP) industry, particularly to O. Vieira, S. H. S. Martinelli and M. A. Betini.