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OPTIMIZATION OF HEAT TRANSFER ZONES IN DISTILLATION COLUMNS

OPTIMIZATION OF HEAT TRANSFER ZONES IN DISTILLATION COLUMNS. X International PHOENICS Users Conference Melbourne, May 2004. Chemtech Solutions. AUTHORS. Chemtech - A Siemens Company, Rio de Janeiro / RJ – Brazil Petrobras / CENPES, Rio de Janeiro / RJ – Brazil. Bruno de Almeida Barbabela

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OPTIMIZATION OF HEAT TRANSFER ZONES IN DISTILLATION COLUMNS

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  1. OPTIMIZATION OF HEAT TRANSFER ZONES IN DISTILLATION COLUMNS X International PHOENICS Users Conference Melbourne, May 2004

  2. Chemtech Solutions

  3. AUTHORS Chemtech - A Siemens Company, Rio de Janeiro / RJ – Brazil Petrobras / CENPES, Rio de Janeiro / RJ – Brazil Bruno de Almeida Barbabela Flávio Martins de Queiroz Guimarães Silvia Waintraub Glaucia Torres

  4. INTRODUCTION • The use of empty spray sections (no packing) in heat transfer regions of vacuum towers allows a high deep cut operation, due to the reduction of the pressure drop along the column. • Simulation studies show that a reduction of 1 mmHg in pressure results in an increase of approximately 0.3% in the gas oils yield. This represents a profit of about US$ 13,000,000 per year for a typical unit with a feed rate of 30,000 m3/day. Other benefits are the decrease in investment and maintenance cost. • Petrobras has four vacuum towers in Rio de Janeiro’s refinery designed by Badger Limited in 1975 without any device in the top pump-around section. In the present work we will present the CFD model developed to analyze this kind of tower.

  5. Spray Nozzles Chimneys INTRODUCTION

  6. GENERAL SETTINGS • PHOENICS VERSION: 3.4 • MULTI-PHASE MODEL: IPSA FULL • INTERPHASE PROPERTIES: By GROUND Coding. • Customization based on PETROX (Petrobras’ Process Simulation Tool) routines for calculation of petroleum fractionsproperties; • SPRAY FORMATION MODEL: By GROUND Coding. • Spray formation sources based on nozzle characteristics;

  7. SIMULATION STRATEGY VALIDATION PHASE Two-dimensional model (simplified) Three-dimensional model OPTIMIZATION PHASE Two-dimensional model (simplified) TUNNING PHASE Three-dimensional model

  8. GEOMETRY – THE EMPTY SPRAY SECTION

  9. GEOMETRY – THE SPRAY NOZZLES

  10. GEOMETRY – THE CHIMNEYS

  11. ANALYSIS – THE CHIMNEYS VELOCITY ISO-SURFASE

  12. CONSTRAINTS • Spray generated droplets have a constant and uniform diameter (though it can change along the tower); • No interaction between droplets; • Since the droplets are very small, they behave as a film, without temperature gradient from the bulk of the droplet to the interface; • The vapor phase has an ideal gas mixture behavior; • Only the main petroleum fractions were considered for the properties calculation; • Diffusive transport of the petroleum fractions into the same phase was not considered.

  13. ENERGY TRANSFER The heat transfer between phases is presented below (without convective and diffusive terms) and was based on the heat transfer of small spherical droplets in a continuous vapor phase: Heat Transfer Coefficient (h) Nusselt Number

  14. MASS TRANSFER The mass transfer follows the model below and was based on the petroleum fractions properties calculated by the PETROX routines: Molar Flux (Ni) Mass Transf. Coef.

  15. ATOMIZATION DROPLET SIZE Sauter Diameter (D32) The Sauter diameter is employed in atomization efficiency studies where mass transfer and chemical reactions are presented. Correlations for the Sauter diameter are presented at Mugele [10] and Lefebvre [12].

  16. VALIDATION

  17. VALIDATION

  18. VALIDATION

  19. VALIDATION

  20. VALIDATION – CONCLUSIONS • The computational model fits well the experimental data for the 2D model, although it must be enhanced for the 3D model. • No significant drag of the oil droplets was notified at the current operational conditions. • From the analysis of the results, the current 60o spray cone seems to be not suitable. A wide range nozzle is recommended.

  21. RESULTS

  22. CAPACITY FACTOR ANALYSISRESULTS – CS = 0.05 ft/s Temperature Velocity

  23. CAPACITY FACTOR ANALYSISRESULTS – CS = 0.10 ft/s Temperature Velocity

  24. CAPACITY FACTOR ANALYSISRESULTS – CS = 0.20 ft/s Temperate Velocity

  25. CAPACITY FACTOR ANALYSISRESULTS – CS = 0.30 ft/s Temperature Velocity

  26. CAPACITY FACTOR ANALYSISRESULTS – CS = 0.325 ft/s Temperature Velocity

  27. CAPACITY FACTOR ANALYSISRESULTS – CS = 0.35 ft/s Temperature Velocity

  28. Height (m) Capacity factor (Cs) RESULTS – SPRAY STABILITY Heat Transfer Height vs. Cs

  29. Dragged Liquid (%) Droplet diameter (micron) RESULTS – DROPLET SIZE Dragged Liquid vs. Droplet Size

  30. WIDE RANGE NOZZLE (90o CONE) RESULTS – CS = 0.14ft/s Temperature Velocity

  31. WIDE RANGE NOZZLE (90o CONE) RESULTS – CS = 0.325ft/s Temperature Velocity

  32. TWO SETS OF NOZZLES (90o CONE) RESULTS – CS = 0.14ft/s Temperature Velocity

  33. TWO SETS OF NOZZLES (90o CONE) RESULTS – CS = 0.325ft/s Temperature Velocity

  34. TWO SETS OF NOZZLES (90o CONE) RESULTS – CS = 0.40ft/s Temperature Velocity

  35. CONCLUSIONS • The maximum capacity factor allowed for spray cone stabilization simulated (between 0.325 and 0.375 ft/s) was similar to the values reported by experimental observations and experts opinions; • Since the simulations showed that the effective height of the heat transfer zone has low dependence on the mean droplet size, it is recommended that the spray nozzles were adjusted to be biased toward the generation of greater droplets in order to minimize the liquid drag; • The use of wider angles of sprays reduces the effective height of heat transfer zone despite the loss of spray stability; • The use of two levels of distributors is recommended for improve the spray cones stability and reduce the effective height of the heat transfer zone.

  36. CONCLUSIONS • Although some improvements have to be made, CFD seems to be an useful tool to analyze the performance of heat transfer and spray formation in vacuum towers. The use of this technology on the optimization of current towers and on the project of new ones is recommended to improve their performance.

  37. NEXT STEPS • Petrobras will use the model to perform other studies: • Variation of the liquid reflux temperature • Variation of the height of the spray nozzles • Calculation of the global heat transfer coefficient • To enhance the model of the petroleum mixture, considering more fractions in it.

  38. Your Success is Our Goal THANK YOU Contact: Flávio Guimarães Senior Manager Tel:+55 (21) 3233-5100 Mail:flavio.guimaraes@chemtech.com.br Kontaktadresse: Peter Muster I&S GC Schuhstraße 60 91052 Erlangen Tel:09131-7-24607Mail:peter.muster@siemens.com www.siemens.com/itps1 www.chemtech.com.br

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