CFD Modeling of Crankcase Inertial Oil Separators. Arun P. Janakiraman Anna Balazy Saru Dawar

Transcription

1 CFD Modeling of Crankcase Inertial Oil Separators Arun P. Janakiraman Anna Balazy Saru Dawar 1

2 Background Emission regulations are becoming stringent and will include blowby emissions. There is a need to vent gases from the crankcase and remove liquid oil and filter aerosol from the blowby gases before its either vented or send back to the turbo. Two technologies engineered at Cummins Filtration Inc. for this purpose are Inertial Oil Separators Coalescing Oil Separators Inertial Impactors are non serviceable parts which usually last the life of the engine. 2

3 Background (contd.) Porous fiber impaction zone Aerosol accelerated by the flow Impactor Nozzle Some amount of flow which enters the media and particles it carries are filtered. Inertial Impactor designed and manufactured at CF Inc. Impactors accelerate the aerosol stream and makes it turn by 90 degrees at the impaction surface. Particles with enough inertia are captured as they cannot make the turn. 3D CAD model of a typical impactor section Impactor Nozzles Impactor media 3

4 Background (contd.) The purpose is to understand the performance of the inertial impactor using CFD. Parameters which constitute performance index are Pressure drop across the device Particle Separation Efficiency ( Fractional and Gravimetric) The flow field and dp can be easily predicted by CFD. Ansys Fluent used for this purpose. Complexity arises in particle separation efficiency prediction due to the media patch. Not all of the flow enters the media. Non uniform velocity distribution through the media. Aerosol transport predicted using Fluent discrete phase model. Filtration inside the media patch needs to be accounted for evaluating overall performance. Strong coupling between flow and particle trajectories. 4

5 Constituent Equations Reynolds Averaged Navier Stokes solved using realizable k-ε closure model. Continuity: Momentum: Turbulence Closure Equations k: ε: Media patch represented by a porous zone with momentum sink term. Darcy s law used for the sink term: 5 Equation of motion for particles/parcels:

6 Constituent Equations (contd.) Mechanisms of single fiber theory particle capture considered are Diffusion: Natanson (1957) E D 2.32 Ku 1 /3 2/3 Pe Stechkina and Fuchs (1966) Interception: E D 2.9Ku 1/ 3 Pe 2/ Pe 1 Stenhouse A Stenhouse B Impaction: E E R R E I Ku 1 N ln 1 N 1 N 1 1 N 1 1 N 3 R R R R R 1 1 N R 1 N R Kn F 1 N R ln 1 N R ln Kn 0.5 ln Stk 3 3 Stk 0.77Stk F 2 2 Overall Efficiency based on Perfectly mixed flow model taking into account fiber diameter distribution Where m =1 3 represents various mechanisms of particle capture, N F is the number of fibers considered. 6

7 Computational Details Only a single nozzle was considered for the analysis Fluent Pressure based Segregated solver used. 2D Axisymmetric assumption for nozzle geometry. Flow assumed to be steady. Pressure Staggering option and 2 nd order upwind schemes used for discretization. SIMPLE algorithm used for pressure velocity coupling. Under relaxation at Fluent default values. Mesh has around 75K cells. Production of k turned off inside the porous zone. Media porosity is constant. Droplet injection done from a rake surface Fluent UDFs incorporating all the single fiber physics inside the porous zone hooked to the simulation. UDFs generalized to run on 2D,3D geometries serial and parallel Fluent. 7

8 Grid Independence and DPM parameters Study (4 Factor 2 level factorial DOE) Fractional Efficiency % 100.0% 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Fine mesh cells Medium mesh cells Coarse mesh 8507 cells Stk# Gravimetric Efficiency % 77.3% Effect of Number of Rake Injection Points 77.2% 77.1% 77.0% 76.9% 76.8% 76.7% 76.6% No. of Rake Points 8

9 Grid Independence and DPM parameters Study (4 Factor 2 level factorial DOE)-contd. Main DPM parameter affecting the particle capture efficiency Gravimetric Efficiency % 79.5% 79.0% 78.5% 78.0% 77.5% Effect of Tolerance on Gravimetric Efficiency Fluent default - 1e % 76.5% 1.00E E E E E E E-05 Tolerance Chosen for subsequent studies

10 Experimental Setup for measuring Pressure drop and Fractional efficiency dp Aerosol generator Part under test Welas particle Counter Upstream Isokinetic Sampling probes Welas particle Counter Downstream Flow meter Absolute Filter Pump 10

11 Results and Discussion Idealized Case to understand whether CFD has captured all the single fiber equations correctly. 0.5 micron diesel liquid aerosol. Amount injected = 1g The below plot shows how the particle stream losses mass as it goes through the media based on single fiber theory 4" Thick Media Fiber Diameter = 4e-5 m Packing Density = Media zone in CFD Efficiency = Mass captured/total Mass Injected kg 11

12 1 Results and Discussion CFD vs. Single Fiber Theory Idealized case Depth Filtration Equations have been captured correctly in the UDFs 0.7 Efficiency Theory CFD Model E E E E E E E-06 Particle Diameter (m) 12

13 Results and Discussion Non Dimensionalized Velocity magnitude contours Flow pathlines colored by non-dim velocity magnitude Flow makes an 90 degree turn as the media acts like a pseudo wall. Non uniform flow distribution through the Not all of the flow enters the media. media. Strong coupling between the flow inside and outside the media. 13

14 Results and Discussion Contours of Non dimensionalized static pressure. Non Dimensionalized dp Non Dimensionalized dp versus flow. y = x R² = Typical rise in static pressure seen close to the impaction surface Non Dimensionalized Flowrate Typical 2 nd order behavior in pressure drop of an inertial loss device captured here by CFD 14

15 Results and Discussion Aerosol trajectories colored by parcel mass variation Total mass injected = 1 g- 200 aerosol streams Mass per stream = 5e-3 g Size of Aerosol Injected = 0.5 micron The CFD model captures all the interaction effects as evidenced in this slide Not all the aerosol streams enter the media Aerosol streams losses a lot more mass here due to capture than through the rest of the media. This is due to the flow distribution and various mechanisms contributing differently based on the local flow conditions. Very strong coupling evidenced between flow and aerosol trajectories 15 kg Due to low Stk# the aerosol follows the flow for most part.

16 Results and Discussion Aerosol trajectories colored by parcel mass variation Total mass injected = 1 g- 200 aerosol streams Mass per stream = 5e-3 g Size of Aerosol Injected = 0.8 micron With increase in particle size and Stk# more particles penetrate the media and are filtered based on single fiber theory kg 16

17 Results and Discussion Aerosol trajectories colored by parcel mass variation Total mass injected = 1 g- 200 aerosol streams Mass per stream = 5e-3 g Size of Aerosol Injected = 1.0 micron Aerosol filtration inside the media visually seen with the color change kg 17

18 Results and Discussion Aerosol trajectories colored by parcel mass variation Total mass injected = 1 g- 200 aerosol streams Mass per stream = 5e-3 g Size of Aerosol Injected = 1.5 micron Particle size at a point were all the aerosol streams enter the media due to their inertia. kg 18

19 Results and Discussion Aerosol trajectories colored by parcel mass variation Total mass injected = 1 g- 200 aerosol streams Mass per stream = 5e-3 g Size of Aerosol Injected = 2.0 micron Further penetration of the aerosol streams into the media as the particle size goes up. kg 19

20 Results and Discussion Aerosol trajectories colored by parcel mass variation Total mass injected = 1 g- 200 aerosol streams Mass per stream = 5e-3 g Size of Aerosol Injected = 2.5 micron Some of the particle streams are completely captured inside the media patch kg 20

21 Results and Discussion Aerosol trajectories colored by parcel mass variation Total mass injected = 1 g- 200 aerosol streams Mass per stream = 5e-3 g Size of Aerosol Injected = 3.0 micron Complete capture of all aerosol streams within the media patch. Criterion for capture depends upon the parcel mass. kg 21

22 100.0 Results and Discussion Fractional efficiency curve constructed based on simulation results at two different flow rates Separation Efficiency % Q1 Q2>Q1 Improvement in efficiency with increase in flowrate typical of inertial separation device captured here by the CFD model. Q Stk # 22

23 Results and Discussion Comparison with test data Pressure Drop Agreement in pressure drop between CFD and test data is very good. 0.7 dp/dp max CFD Model Test V/V max 23

24 Results and Discussion Comparison with test data - Efficiency Flow Rate = Q Separation Efficiency % Very close agreement between CFD and test data for fractional efficiency at this flow rate. Quite surprising result considering the simplicity of the model. Test CFD Model Stk # 24

25 Results and Discussion Comparison with test data - Efficiency Flow Rate = Q Separation Efficiency % CFD Model Higher efficiency predicted by CFD than test at this flowrate. Due to the high velocities seen through the nozzle it might be quite possible for aerosol reentrainment into the air stream. This is not captured here by the CFD model. Test Stk # 25

26 Results and Discussion Ultra Fine Aerosol Particle Size Distribution entered in Fluent using Rosin Rammler Distribution Mass Fraction > d ISO Ultrafine Aerosol Distribution Rosin Rammler Distribution In order to understand gravimetric efficiency performance ultra fine aerosol distribution used in lab tests was injected in Fluent Particle Size (microns) 26

27 Results and Discussion Overall good agreement with test data Gravimetric Efficiency (%) Test CFD Range of operation Flow Rate (m 3 /hr) 27

28 Conclusions The single fiber theory has been successfully incorporated into CFD through the use of Fluent UDFs. The model was tested against the single fiber theory and was found to be spot on indicating that all the equations have been correctly captured in the Fluent UDF. Reasonably good agreement between CFD and test for Fractional Efficiency. Gravimetric efficiency prediction by the model is found to be reasonably close to test data for impactors. Model can be used with enough confidence for optimization studies. 28

29 Acknowledgement The authors gratefully acknowledge the support of Cummins Filtration Inc. in this work. They would like to personally thank Bryan Steffen, and Shiming Feng for their assistance. 29

30 Questions? 30