Modeling Ethylene Glycol Pulping of Vine Shoots

Authors

  • Luis Jiménez
  • Victoria Angulo
  • María Jesús de la Torre
  • Antonio Pérez
  • Sebastián Caparrós

Keywords:

Vine shoots, pulping, ethylene glycol, polynomial modelling, neural fuzzy modeling

Abstract

The influence of the operational variables in the pulping of vine shoots by use of ethylene glycol [temperature (155-185 °C), cooking time (30-90 min) and ethylene glycol concentration (50-70% v/v)] on the pulp properties is discussed. In particular, the yield, kappa number, viscosity, and drainability were studied.

Using a face-centered central composite factorial design and the software BMDP and ANFIS Edit Matlab 6.5, we developed polynomial and fuzzy neural models that reproduced the experimental results of the dependent variables with errors less than 5%. Both types of model are therefore effective with a view to predicting the ethylene glycol pulping process.

Based on the proposed equations, the best choice is to use values of the operational variables resulting in near-optimal pulp properties while saving energy and immobilized capital on industrial facilities by using lower temperatures and shorter processing times. One combination leading to near-optimal properties with reduced costs is using a temperature of 170 °C and an ethylene glycol concentration of 70% for 60 min.

References

Angulo, V., and E. García, E. 2005. Caracterización de la madera de sarmientos de vid con vistas a su aprovechamiento papelero. Viticultura/Enología Profesional96:34-42.nAtchison, J. E. 1998. Update on global use of non-wood plant fibers and some prospects for their greater use in the United States. North American Non-Wood Fiber Symposium. Atlanta, GA.nBard, J., J. Patton, and M. Musavi. 1999. Using RBF neural networks and fuzzy logic controller to stabilize wood pulp freeness. Int. Joint Conf. On Neural Networks '99.6:4247-4252.nDíaz, M. J., A. Alfaro, M. M. García, M. E. Eugenio, J. Ariza, and F. López. 2004. Ethanol pulping from tagasaste (Chamaecytisus proliferus L.P. ssp palmensis). A new promising source for cellulose pulp. Ind. Eng. Chem. Res.43(8):1875-1881.nGilarranz, M. A., M. Oliet, F. Rodríguez, and J. Tijero. 1998. Ethanol-water pulping. Cooking variables optimization. Can. J. Chem. Eng.76(2):253-260.nHergert, H. L. 1998. Developments in organosolv pulping. An overview. Pages 5-67 in R. A. Young and M. Akhtar eds. Environmental friendly technologies for the pulp and paper industry. John Wiley and Sons Inc., New York, NY.nJang, J. S. R., C. T. Sun, and E. Mizutani. 1997. Neurofuzzy and soft computing: A computational approach to learning and machine intelligence. Prentice Hall, New York, NY.nJarvensivu, M., E. Juuso, and O. Ahava. 2000. Intelligent supervisory-level control of industrial processes. Paperi ja Puu86(2):386-391.nJiménez, L., E. Navarro, I. Pérez, and F. Maestre. 1997a. Disponibilidad, almacenamiento y caracterización de residuos agrícolas para la fabricación de pastas celulósicas para papel. Investigación y Técnica del Papel131:130-152.nJiménez, L., F. Maestre, M. J. De La Torre, and I. Pérez. 1997b. Organosolv pulping of wheat straw by use of methanol-water mixtures. TAPPI J.80(12):148-154.nJiménez, L., F. Maestre, and I. Pérez. 1999. Use of butanol-water for making wheat straw pulp. Wood Sci. Technol.33(2):97-109.nJiménez, L., M. J. De La Torre, FM. J., F. Maestre, J. L. Ferrer, and I. Pérez. 1997c. Organosolv pulping of wheat straw by use of phenol. Bioresource Technol.60(3):199-205.nJiménez, L., M. J. De La Torre, J. L. Bonilla, and J. L. Ferrer. 1998a. Organosolv pulping of wheat straw by use of acetonewater mixtures. Process Biochem.33(4):401-408.nJiménez, L., M. J. De La Torre, F. Maestre, J. L. Ferrer, and I. Pérez. 1998b. Delignification of wheat straw by use of low-molecular-weight organic acids. Holzforschung52:191-196.nJiménez, L., I. Pérez, M. J. De La Torre, F. López, and J. Ariza. 2000. Use of formaldehyde for making wheat straw cellulose pulp. Bioresource Technol.72:283-288.nJiménez, L., I. Pérez, J. C. García, and A. Rodríguez. 2001. Influence of process variables in the ethanol pulping of olive tree trimmings. Bioresource Technol.78(1):63-69.nJiménez, L., I. Pérez, F. López, J. Ariza, and A. Rodríguez. 2002. Ethanol-acetone pulping of wheat straw. Influence of the cooking and the beating of the pulps on the properties of the resulting paper sheets. Bioresource Technol.83(2):139-143.nJiménez, L., A. Rodríguez, M. J. Díaz, F. López, and J. Ariza. 2004. Organosolv pulping of olive tree trimmings by use of ethylene glycol/soda/water mixtures. Holzforschung58(2):122-128.nLampela, K., L. Kuusisto, and K. Leiviska. 1996. D100-stage bleaching control with fuzzy logic. TAPPI J.79(4):93-97.nMyers, R. H., and D. C. Montgomery. 1995. Response surface methodology: product and process optimization using designed experiments. John Wiley and Sons, New York, NY.nMore, A., and A. Toraldo. 1989. Algorithms for bound constrained quadratic programming problems. Numer. Math.55:377-400.nMusavi, M. T., C. Domnisoru, G. Smith, D. R. Coughlin, and A. L. Gould. 1999. A neuro-fuzzy system for prediction of pulp digester K-number. Int. Joint Conf. Neural Networks '99.6:4253-4258.nMuurinen, E. 2000. Organosolv pulping. A review and distillation study related to peroxyacid Pulping. Doctoral thesis, Department of Process Engineering, University of Oulu, Finland.nNilson, L., and M. Dobel. 1998. High-level control of the lime kiln and the causticizing process. Int. Chem. Recovery Conf. Tampa-1998.2:537-545.nNormas Une. 1989. Instituto Nacional de Racionalización del Trabajo. Madrid.nPulkkinen, M., M. Saastamoinen, and M. Skytta. 1997. Neural networks and fuzzy logic control of oxygen delignification. Paperi j Puu79(3):152-154.nTappi Standards. 1997. TAPPI Test Methods. Atlanta.nTjeerdsma, B. F., F. H. A. Zomers, E. C. Wilkinson, and R. Sierra-Alvarez. 1994. Modeling organosolv pulping of hemp. Holzforschung48(5):415-422.nVega, A., M. Bao, and J. Lamas. 1997. Application of factorial design to the modeling of organosolv delignification of Miscanthus-sinensis (Elephant grass) with phenol and dilute-acid solutions. Bioresouce Technol.61(1):1-7.nWaller, A. 1999. Influence of processing on mechanical pulp. Mechanical pulping trends. Appita Annual General Conf. Proceedings '99.53(2):391-396.nWasik, L. S, G. R. Mitted, and D. J. Nelson. 2000. Controlling brownstock washing during production rate changes. TAPPI J.83(3):94-101.nWillems, J., and M. Williamson. 1996. Bleach plant operations, equipment and engineering. Sensors and process control. Pulp Bleaching 625-645.nWise, L. E., M. Murphy, and A. D'Adieco. 1946. A chlorine holocellulose, its fractionation and bearing on summative wood analysis and studies on the hemicellulose. Paper Trade J.122(2):35-43.nWorks, G. A. 1989. Neural network basics. Proc. AUTOFACT' 89 29-1-29-9.nYu, Q., L. Huanbing, Z. Xiaoping, and P. J. C. Tessier. 1997. Optimization of a wood chip refining process based on fuzzy relational models. Computers Chem. Eng.21:1127-1142.nZadeh, L. A. 1965. Fuzzy sets. Information and Control8:338-353.n

Published

2007-09-27

Issue

Section

Research Contributions