Computational Fluid Dynamic Modeling Applications

Transcription

1 Computational Fluid Dynamic Modeling Applications Canadian Heavy Oil Conference Dr. Marvin Weiss

2 What is CFD Computational Fluid Dynamics Colorful Fluid Dynamics Colors For Directors Carefully Fitted Data

3 CFD - Overview Validation Data CFD Solver Mesh Generation Boundary Conditions No Physical Properties & Models Convergence Check Yes Visualization Governing Equations HPC Platform 6 PhDs Coanda s Linux Cluster (500+ Cores) 3

4 Solver Synopsis 4

5 HPC - High Performance Computing 5

6 Project Examples Determination of Cv for Large Valves (>12-inch) Open Channel Flow/Wear of Liquid-Solid Slurry Separation Vessels with Rotating and Stationary Devices 3D multiphase flow in rotating frames Mixing of non-newtonian Fluids Steam/Oil Heating and Condensation Multiphase compressible flow with phase change 6

7 Project Examples Sludge Mobilization using Submerged Jets Transient Sand Build-up and Cleaning Diesel Flushing of Bitumen Multi-component flow of non-newtonian fluids Flashing Flow through Nozzles Multi-phase flow with phase change Supersonic Gas Flaring Compressible gas flow with combustion and radiation 7

8 Project Examples Bubble Column Flotation Systems Fluidized Bed Reactors Transient Hydrocyclone Flow Large-Scale Water Intake Systems Free surface flows 8

9 Standards ANSI/ISA Control Valve Capacity Test Procedures 9

10 Standards ANSI/HI Pump Intake Design 10

11 Standards ANSI/HI Pump Intake Design 11

12 Liquid-Solid Slurry Flow Distributor Even redistribution of launder flow into multiple radial streams Models Used Multiphase VOF (Volume of Fluid) Multiphase granular models 12

13 Liquid-Solid Slurry Flow Distributor Original Modified 13

14 Liquid-Solid Slurry Flow Distributor 14

15 Erosion in Open Channel Flow Mixing and redistribution of slurry flows Models Used Multiphase VOF DPM (Discrete Phase Model) Species transport Multiphase granular models 15

16 Erosion in Open Channel Flow 16

17 Erosion in Open Channel Flow Free Surface Contours Erosion Rates 17

18 Polymer Injection - Overview Mixing of a Non-Newtonian polymer into a Non-Newtonian fluid Models Used Species Transport with reaction Non-Newtonian fluid properties Two competing reactions 18

19 Polymer Injection Results 19

20 Polymer Injection Results 20

21 Separation Vessels Separation efficiency in a gravity separator Models used Eulerian multiphase Dense particle model 22

22 Separation Vessels 23

23 Separation Vessels Velocity Vector Stream Function Solid Concentration 24

24 Separation Vessels Axial Velocity CFD vs. Experiment CFD (single Phase) 25

25 Separation Vessels Radial Velocity CFD vs. Experiment CFD (single Phase) 26

26 Separation Vessels 27

27 Separation Vessels 28

28 Validation Coanda Labs Broad experience in many areas of industrial fluid dynamics Oil and gas, petrochemicals, plastics, pharmaceuticals, atmospheric dispersion, oil sands, fuel cells State-of-the-art physical modeling Design Engineering and Instrumentation Development facilities Recognized for rapid turn-around times and exceptional IP protection 5000 m 2 of laboratory and office space across 3 locations in Western Canada 29

29 Coanda Our research teams bring together scientists, engineers, and technologists to tackle tough fluid dynamics challenges. Multidisciplinary teams provide unique solutions and insight. Our highly integrated teams are classified in three major groupings: Senior Scientific and Industrial Applications Team Applied Research Group CFD Engineering & Projects Applications Group 30

30 Specific Benefits of CFD Modeling Single-phase fluid problems can usually be solved very accurately and at much lower cost than experiment Complex (i.e. multi-phase, etc.) simulations and parameter studies provide quantitative insight once validated CFD can be a very effective technique to solve important optimization problems 31

31 Benefits of Fluid Dynamics Modeling Cost effective platform for knowledge building Useful in existing and new technology Highly complex fluids and systems can be modeled Avoids hazardous field environments Utilization of advanced measurement techniques Rapid design optimization Extended parameter ranges Scale-up analysis Proven history Training & technology transfer 32