numerical simulation of subcooled nucleate boiling 2013-01 ... · for flow boiling the bulk fluid...

ABSTRACTThere has been a change in the thermal management of ICengines where engineers now like to harness the superior heattransfer rates available when limited and controlled nucleateboiling is used to remove heat from high temperature zones.Any flaws in the design of such systems, such as uncontrolledboiling that leads to Dry Out situation, can have an adverseeffect on the cooling performance. A detailed engineeringmodel of this process would allow engineers to weed outflawed designs early in the design process. In this paper, weproposed and validated a CFD model for this process.

A CFD model is built using the commercial CFD solverANSYS FLUENT. The mixture multiphase model is used tostudy subcooled nucleate boiling in IC engine coolingjackets. The departure of bubbles enhances heat transfer atwalls, which is captured using the empirical correlation.Volumetric mass transfer is modeled using the inbuiltevaporation-condensation model. Results obtained from heattransfer in channels are compared with experimental resultsavailable in the literature for a range of operating pressures,different inlet sub-cooling and different inlet flow velocities.The predicted heat fluxes are in good agreement withexperimental data. Results from a typical I.C. engine coolingjacket geometry are also presented.

INTRODUCTIONCooling plays an important role in optimal performance of anIC engine. Insufficient cooling results into degradedperformance, reduced power and, in long run, may result intoengine failure due to wear, cracking or warping. Theobjectives of IC engine cooling jacket design are as follows:

• Keep wall temperatures of different components withinacceptable levels to avoid loss of power and failure due tothermal stresses.

• Avoid flow maldistribution in the cooling jacket. Sinceengine jacket has complex flow passages, there is apossibility of stagnant zone or high velocity zones. While theformer may cause hot spots, the latter may result in higherpressure drop.• Minimize the pressure drop

For IC engine cooling, typical coolant used is aqueousethylene glycol (an anti-freeze mixture). Its boilingtemperature ranges from 108 C to 142 C, for a pressure rangeof 1 bar to 3 bar, and 50/50Vol% composition. Coolanttemperature at the inlet is typically maintained at 90 C [1],which is very close to boiling temperature. Hence, there is apossibility of coolant boiling inside the cooling jacket,especially in the regions of high heat flux, e.g. walls near theexhaust port, fire deck etc.

Depending on the regime of boiling, it may have favorable oradverse effect on the cooling jacket performance. As long asthe cooling wall temperature is below the boilingtemperature, there is no boiling. Up to certain walltemperature above the saturation temperature, the boilingtakes place in form of bubbles only. This is called nucleateboiling and it is desired mode for any so-called boiling basedcooling system as it increases the overall heat transfercoefficient. At higher wall temperatures, the vapor forms afilm over the wall. This is called Dry-Out situation, whichreduces the local heat transfer coefficient significantly. Ascooling jacket has horizontal passages and has a complexshape, there is a possibility of stratification of vapor forminga film, which creates local vapor pockets/vapor trap near thewall. This is similar to Dry-Out situation encountered in flowboiling and has the same effect, i.e. reduction of local heattransfer coefficient.

As mentioned earlier, nucleate boiling occurs locally incooling jackets and the engine designers are aware of this

Numerical Simulation of Subcooled Nucleate Boilingin Cooling Jacket of IC Engine

2013-01-1651Published

04/08/2013

Hemant Punekar and Saurish DasAnsys Inc,

Copyright © 2013 ANSYS Inc.

doi:10.4271/2013-01-1651

Downloaded from SAE International by ANSYS Inc, Monday, September 14, 2015

http://dx.doi.org/10.4271/2013-01-1651

fact. The recent trend is to make more deliberate use of thenucleate boiling and at the same time avoid Dry-Out situationto further optimize the cooling jacket design.

CFD is one of the most powerful tools to gain insight of theflow and heat transfer process. With appropriate modeling ofthe boiling phenomenon, it is possible to know the wallsuperheat, regions of boiling and regime of boiling.Considering two phase system, it is possible to model vaportransport with in the cooling jacket and locations of vaportrapping and stratification. With all these advantage, it is alsoworth noting here that the accuracy of CFD results dependson the accuracy of the model used to describe the physicalprocess, use of suitable grid resolution and properconvergence.

LITERATURE REVIEWWith the help of increased computational resources, now ithas become possible to simulate bubble growth near theboiling wall [2, 3, 4], but such studies are restricted to a smallnumber of growing bubbles on a simple geometry with idealsurfaces. Such model-free numerical prediction for boiling ina real world engineering problem is far beyond the scope oftoday's computational power. Moreover due to limitedunderstanding of near wall phenomenon of boiling, someresearchers [5, 6] even consider it rather as an unpredictablechaotic process that causes fluctuations of wall heat fluxand/or wall temperature. The engineering need to predictboiling heat transfer in real life applications motivated severalresearchers, CFD analysts and design engineers to developboiling heat transfer models based on experimentalcorrelations, which involve a great deal of empiricism totackle the effect of surface roughness, surface fluidcombination, surface initial condition etc. For most of thecomplex engineering cases people rely on experimentalcorrelations for boiling heat and mass transfer derived for aparticular situation.

To predict nucleate boiling, a great variety of “singleequation” “1-D” wall heat flux models are available in theliterature. These models make use of bulk propertiesaveraged over a cross-sectional area, normal to the meanflow, and a set of correlations based on experimental data forwell-established flow (e.g. fully developed parallel flowwithout any swirl, separation, wake etc.). Those existingsingle equation 1-D models can be broadly grouped into twocategories:

• General empirical correlations, which correlate the wall heattransfer rates or heat transfer coefficient with wall super heatthrough non-dimensional groups [7, 8, 9, 10].

• Mechanistic models or partitioning models, which attemptto capture total heat transfer by dividing it into single phaseconvective heat transfer part and boiling evaporative heattransfer part obtained from experiments [1, 2, 11, 12, 13, 14,15, 16].

As mentioned earlier, all these models are created andvalidated in simple geometries, like pipe, rectangular duct orin annular section. Sometimes a complex 3-D problem likeengine cooling jacket is simplified to 1-D problem, in whichit is represented as a channel of equivalent hydraulic diameterand these models are used[15, 16]. To get spatial and/ortemporal variation of temperature and vapor fraction, some ofthese models are extended and implemented in 3-D CFDsolver. Despite their more physical basis, they still involve agood deal of empiricism.

Over the last two decades, the two-fluid multiphase methodwith the so called RPI wall boiling model, developed byKurul & Podowski [17] in Rensselaer Polytechnic Institute,has been established as the modeling approach formechanistic prediction of boiling phenomena. In our previouswork [18] we had discussed the implementation of RPI wallboiling model in ANSYS FLUENT and its validation. It is adetailed boiling model that works with eulerian multiphasemodel, considering various sub-mechanisms of boiling likenear wall bubble dynamics and heat flux partitioning. Thismodel is widely used to investigate boiling in conditionsfound in the nuclear industry [17, 18], which is high pressuresteam-water systems. Some researchers also have observedthat it is difficult to use RPI approach at lower operatingpressures [19].

In recent years a few researchers have carried out 3-D CFDinvestigations focusing on the boiling heat transfer analysis ofthe I.C. engine cooling jacket. Tao Bo [20] implemented areduced order boiling model in CFD environment andvalidated with experimental data. This mechanistic modeluses Rohsenow's pool-boiling correlation [14] to predict theflow boiling. It neither accounts the effect of bulk velocity ofthe flow nor considers modification of the empiricalcorrelation for flow boiling. Srinivasan [21] used similarapproach for boiling of pure water, but for evaporative heattransfer coefficient Chen's correlation [22] was used. It hadbeen implemented in Euler-Euler multi-fluid frame work andit used empirical correlations for near wall bubble dynamics.Euler-Euler multiphase model solves transport equations foreach phase which makes it computationally expensive. Chen'scorrelation has also been employed by Fan et al. [23].

Thus, there is a significant research work going on to developa wall boiling model which can be used for low pressureboiling conditions typically encountered in cooling jacketapplication. Each model has its own unique advantages anddisadvantages. In the present work, a wall boiling model isdeveloped in mixture multiphase frame work. This newlydeveloped model is robust, computation friendly andreasonable accurate for design comparison/ optimization. It isvalidated for aqueous ethylene glycol anti-freeze mixtureflowing over a rough cast aluminum alloy surface that hasproperties similar to the passages of a cooling jacket oftypical IC engine. This model is applied to a real life cooling


jacket geometry with typical conditions and obtained resultsare discussed.

POOL BOILING AND FLOWBOILINGIt is worth to describe in detail the flow boiling phenomenonand boiling regime transaction as compared to pool boiling.First detailed study for pool boiling was conducted byNukiyama [24] using an electric heated platinum wireimmersed in a pool of liquid. He broadly categorized it intosingle phase natural convection region, nucleate boiling,transition boiling and film boiling. During nucleate boiling,due to bubble departure induced micro convection in thethermal boundary layer heat transfer rate from thesuperheated surface to liquid pool gets increased. For the caseof flow boiling where liquid is forced to move by an externalsource, the basic mechanisms of heat transfer are same, but itoccurs at a higher heat flux compared to pool boiling. Alsofor flow boiling the bulk fluid velocity plays a crucial role inheat and mass transfer mechanism. Another importantdifference for flow boiling in the internal ducts, as reportedby Robinson et al. [1], is the bubble condensation in the mainbulk flow. For pool boiling, departed bubbles rise up andescape to free surface of the liquid pool. Whereas for flowboiling some of the bubbles get condensed in the bulk liquidand the rest of the bubbles, depending upon heat flux, createdifferent two phase flow regimes like, bubbly flow, slug flow,annular flow etc.

As stated earlier, the present work is aimed at developing andvalidating a CFD model for nucleate flow boiling which iscommonly encountered in thermal management of enginejacket cooling application. Unlike pool boiling, the total wallheat transfer coefficient in flow boiling in an internal duct is asummation of single phase forced convective heat transfercoefficient and evaporative heat transfer coefficient due tophase change. In other word pool boiling is special case offlow boiling where bulk velocity is zero, i.e. single phaseforced convection is absence. Increased bulk flow velocitysuppresses the bubble growth and/or bubble departure fromthe superheated surface, as a result evaporative heat transfercoefficient gets reduced; on the other hand it increases singlephase forced convective heat transfer coefficient. In theFigure 1, formation of bubbles near the wall during flownucleate boiling is shown for different bulk velocities but forsame wall superheat, working fluid (water) and operatingpressure. This experimental work by Andrew O'Neill [25]explicitly shows that with increase in velocity for same otherconditions the size and number of generated bubbles getdecrease, i.e. suppression of boiling due to increase in bulkfluid velocity. Both these phenomena i.e. with increasingflow velocity increase of convective heat transfer andsuppression of nucleate boiling are considered in presentwork by implementing Chen's 1-D model in 3D CFDenvironment.

Figure 1. Experimental images for bubble formationduring nucleate boiling of water over a heated plate. For

same operating pressure, wall superheat and surfacefluid combination these images indicate the suppression

of nucleate boiling with increase in bulk velocity [25]

Although some researchers have extended Rohsenow'scorrelation to account for forced convection boiling [20], thiscorrelation was originally developed for pool boiling [14].Chen's correlation [22] was developed for forced convectionboiling conditions. It introduces factors to take care ofenhancement of convective heat transfer to liquid due tomicro convection near the vapor bubbles and suppression ofnucleation heat flux due to forced convection. More detailabout this model is described in the elater section.

NUMERICAL METHIODOLOGYTo model subcooled nucleate boiling, it is necessary tosimulate two phase fluid flow, account for the heat transferaugmentation at the wall and model the mass transferbetween the liquid and gaseous phase. The present boilingmodel is developed using the CFD solver ANSYS FLUENTthat solves a set of governing equations for two phase multi-fluid flow. To model the wall boiling phenomenon modifiedChen's boiling correlation is used to calculate heat transfer atthe wall. A mass transfer model in built in ANSYS FLUENTis used to model the phase change process.

Governing Equations for MultiphaseFlow ModelThe mixture multiphase model in ANSYS FLUENT[26]canmodel “n” phases by solving the momentum, continuity, and


energy equations for the mixture and the volume fractionequations for the secondary phases. The generalized mass,volume fraction for secondary phase, momentum and energygoverning equations have the following forms, respectively:

Mass Conservation & Volume FractionEquation for Vapor Phase

(1)

where is the mass averaged velocity:

(2)

and ρm is the mixture density:

(3)

Here subscript “m” indicates the overall mixture phase and nis the number of phases in a system. α ρ and are volumefraction, density and velocity vector.

From continuity equation for secondary phase p, volumefraction equation for the secondary phase is obtained:

(4)

Momentum Conservation

(5)

where p is pressure, is the gravitational acceleration vector

and is the body force. μm is the viscosity of the mixture:

(6)

Where μt,m is the mixture turbulent viscosity, discussed in theTurbulence Models section below.

In Equation 5, Vdr,k is the drift velocity for secondary phase:

(7)

Energy Conservation

(8)

Where, SE is any volumetric source, Ek is sensible enthalpyand keff is the effective conductivity:

(9)

where kt is the turbulent conductivity, defined according tothe turbulence model.

Turbulence ModelANSYS FLUENT offers a range of 2-equation turbulencemodels. RNG k-ε model is used for this current work. Thegeneral form of k and ε equations for this model are asfollows:

(10)

(11)

In above equations, μt,m is the mixture turbulent viscosity:

(12)

For near wall regions Enhanced Wall Treatment is used alongwith default turbulence model constants. For more detailsplease refer to [27] and [28].

To ensure convergence, default scaled residual convergencecriteria (For mass, momentum and turbulence equations 1e-3and for energy equation 1e-6) are used. In addition to this,mass and energy flux balances are also ensured.

Wall Boiling ModelIn this work, wall boiling model is used to calculate total heattransfer at the boiling wall.


Chen's CorrelationChen [22] reviewed a large amount of other researchers' dataand correlation of flow boiling heat transfer; and came upwith single equation, where total heat flux is partitioned intotwo parts,

(13)

In this equation ‘h’ is the heat transfer coefficient, subscripts‘nuc’ and ‘conv’ corresponds to nucleate boiling andconvection respectively. For nucleate boiling heat transfercoefficient modified Forster & Zuber's pool boilingcorrelation [29] was used. For convective heat transferDittus-Boelter turbulent heat transfer correlation was used,where to calculate Reynolds Number inlet plug velocity andhydraulic diameter of the channel was proposed.

The Nucleate boiling heat transfer coefficient is written as

(14)

Where Cp is the specific heat, σ is the surface tension, L isthe latent heat for vaporization. Subscripts l and gcorresponds toliquid and gaseous phases. Twall and Tsatrelates to wall and saturation temperature. pwall and psatindicate saturation pressure corresponding to Twall and Tsat. Sis the suppression factor ranging from 0 to 1, originallypresented with a graph by Chen and later suggested with abest fit curve by Collier, J.G. [24] as

(15)

Equation 15 indicates the increase of S with decrease inReynolds Number and when Re = 0, S = 1 (pool boilingsituation). Please note that here Re is defined based on liquidproperties, bulk velocity of the liquid and hydraulic diameterof the duct.

Convective heat transfer co-efficient, hconv proposed by Chenas,

(16)

In this equation, hconv,DB is the convective heat transfercoefficient taken from Dittus-Boelter turbulent flowcorrelation and an extra factor F (always greater than 1) isintroduced to encounter the effect of turbulent generation dueto disrupting of the adjacent wall fluid layer during bubble

departure and lift-off. Some researcher [12, 13] also justifiedit as creation of additional surface roughness by bubbles atthe wall, which increase the turbulent level and hence heattransfer. hconv,DB and F are calculated as follows:

(17)

(18)

(19)

where x represents the area averaged void fraction of thechannel.

With Equation 16, the single phase heat transfer componentof the total wall heat transfer can be rewritten as follows:

(20)

While solving energy equation, ANSYS FLUENT solvesnear wall heat transfer, from which qsingle phase can beobtained, however this does not include any enhancement forboiling. Since this internally calculated quantity is available,qsingle phase is used as follows:

(21)

It is worth noting here that unlike 1-D Dittus-Boeltercorrelation which is applicable only to channels of uniformcross-section (constant hydraulic diameter), in ANSYSFLUENT the convective heat transfer is calculated locally ateach wall face based on the local fluid properties andturbulence quantities. Thus, the formulation proposed inEquation 21 extends the applicability of this boiling model toany arbitrary shaped domain.

Mass Transfer ModelANSYS FLUENT offers Evaporation-Condensation model tosimulate phase change process between liquid and gaseousphases. This model takes care of the phase change near thewall as well as inside the domain. It is a mechanistic modeldescribed in ANSYS FLUENT Theory Guide [26, 30].

Based on the mixture temperature Tm, mass transfer can bedefined as follows:

If Tm > Tsat


(22)

If Tm < Tsat

(23)

In Equation 22 & 23, Cevap and Ccond are the evaporation andcondensation frequencies respectively. For more details,please refer to [26] and [30].

VALIDATION CASEThe experimental data from Robinson's work [1] is used tovalidate the current approach for the variation of wall heatflux versus the changes of the wall temperature underdifferent pressures, flow velocities and degree of inlet sub-cooling. In this work by Robinson the motivation was todevelop 1-D model for engine jacket cooling, so typical anti-freeze coolant mixture, 50% aqueous ethylene glycol is used.Both surface finish and surface fluid combination areimportant parameter for boiling, so to replicate the boilingscenario similar to engine jacket, cast from an aluminumalloy is used for the heated plate.

Figure 2. Computational domain to replicate Robinson'sexperimental work [1]

In the Figure 2 computational domain is shown, which iscreated to mimic the experimental set up. The main flowchannel is horizontal, 241mm long and has a rectangularcross section of 16×10mm2. The heating surface is at thebottom of the flow channel, 10×50 mm2, and located 76 mmdownstream from the entrance of the channel. Two inletvelocities of 0.25 m/s and 1m/s are chosen for the validationstudy, in which operating pressure is varied from 1 bar to 3bar and wall temperature is varied from 90 C to 170 C. Outletboundary is set as pressure outlet with zero gauge pressure.All the walls are set as adiabatic expect for the heated wallthat has specified temperature boundary condition.

To ensure grid independence, three meshes with hexahedralcells of size 6×16×200, 8×16×200 and 10×16×200 are used,which are referred to as Mesh-1, Mesh-2 and Mesh-3

respectively. The mesh refinement direction is normal to theheated wall. All the three meshes are used for both thestudies; however, the all the results are reported only for inletvelocity of 0.25m/s. For 1m/s case, results from Mesh-3 arereported.

Simulations can be run in either steady state or in a transientmode; however in this validation we vary the temperature ofthe heating surface and evaluate the surface heat flux fromthe steady state simulation. The variation of coolantproperties with temperature is very important input for thisstudy which is taken form NIST and Robinson's work [1].

Figure 3. Comparison of total heat flux predicted by thepresent model against the experimental observations fordifferent wall temperature, inlet velocity = 0.25 m/s, inlet

temperature = 90 C, pressure = 1bar, 2 bar and 3 bar.Vertical dashed lines are indicating the saturating

temperature for respective operating pressure

Figure 3 shows the comparison of experimental andnumerical results of wall temperature verses wall heat flux atinlet plug velocity of 0.25 m/s and inlet temperature of 90 Cwith different operating pressuresand different walltemperatures. The most important effect of pressure on theboiling heat transfer is through its close association with thesaturation temperature. When the inlet and wall boundaryconditions are given, the saturation temperature determinesthe degrees of superheating, and hence the onset and theintensity of boiling. The saturated temperatures associatedwith the pressures of 1 bar, 2 bar and 3 bar are 108 C, 128 Cand 142 C respectively. The vertical dash lines are indicatingthe same for respective temperature. It is expected that beforethe wall temperature reaches the saturation temperature, i.e.before onset of nucleate boiling, wall heat flux increaseslinearly with wall temperature, which indicates constant valueof heat transfer coefficient at non-boiling zone. The curvesstart differing from its linear behavior in the nucleate boilingzone and higher value of wall heat flux indicates theenhancement due to nucleate boiling.


Figure 4. Comparison of total heat flux predicted by themodel against the experimental observations for differentwall temperature, inlet velocity = 1 m/s, inlet temperature= 90 C & 120 C, pressure = 3 bar. Vertical dashed line isindicating the saturating temperature for 3 bar operating

pressure

Figure 4 represent the similar variation for higher flowvelocity of 1 m/s at 3 bar operating pressure for different inletsub-cooling. The vertical dotted line indicates the saturatingtemperature correspondent to 3 bar pressure. The suppressionof nucleate boiling for high velocity can easily be verified bythe linearity of the curve even beyond the saturationtemperature.

Wall function treatment for near wall boundary layer,refining the mesh not necessarily produces solution ofincreasing accuracy. The wall y+ value is maintained in-between 30 to 200 to put the near wall first cell centroid inthe ‘Logarithmic Layer’ [26, 27] and Enhanced WallTreatment is used. A very good y+ independent/ meshindependent results are observed, where for a constant walltemperature maximum heat flux deviation is within 3.5% fordifferent meshes.

In the numerical results, some deviation from theexperimental results is observed at 1 bar and 2 bar pressuresat low wall superheat (Figure 3). Although this difference ishigh in terms of heat fluxes, it is within 10 K in terms of walltemperature. The accuracy in terms of range of temperature ismore important in the context of engine cooling jacketanalysis, because the heat flux coming from the engine isknown and the aim is to solve conjugate heat transferproblem and find out the cooling jacket temperature. For suchan application, this level of accuracy in temperature isconsidered acceptable, considering the fact that nucleateboiling is a very complex phenomenon, which depends notonly on surface roughness and surface fluid combination, butalso on time history of the boiling surface [1, 6, 7].

APPLICATION: BOILING IN ENGINECYLINDER HEAD COOLINGJACKETA real-life simulation case is presented in Figure 5 todemonstrate the application of the present method to theanalysis of flow in the engine cooling jacket, which alsoinvolves boiling. A partial geometry of single cylinder ICengine is considered, which represents the cylinder head. Itconsists of three fluid zones (cooling jacket, exhaust port andintake port) and one solid zone. Air-Fuel mixture comes in tothe engine cylinder through intake port and high temperaturecombustion products leave the cylinder through exhaust port.A cooling jacket is casted/ bored in cylinder head block,through which the coolant is pumped. The outlet of thisjacket is connected to radiator, where it cools down and usinga coolant pump, it fed back to the inlet of the jacket.

Figure 5. Computational domain for engine coolingpassage conjugate heat transfer simulation. It comprisesthree different fluid zones: Cooling Jacket, Intake Port,

Exhaust Port and solid Engine Block

In this Conjugate Heat Transfer (CHT) study the cylinder andadjacent cooling jacket is not considered. However, to mimicthe actual IC engine situation, a time averaged heat fluxprofile is specified as boundary condition to the fire decksurface of the engine block. This profile is obtained from thecombustion simulation of a Direct Injection CompressionIgnition engine using typical conditions, which is carried outusing Diesel Unsteady Laminar Flamelet Model (DUFL)


available in ANSYS FLUENT. In the Figure 6, contours oftime averaged heat flux profile at the fire deck surface isshown.

Figure 6. Engine Block and time averaged heat fluxprofile from Diesel Unsteady Laminar Flamelet Model

(DUFL) available in ANSYS FLUENT

Uniform tetrahedral mesh-elements with two inflation layersat the fluid walls are generated. As mentioned earlier, nearwall first cell height is chosen such a way that it remain in theLog-Law-Region of the boundary layer i.e. 30 < y+ < 200.Total mesh count reported as 3.8 million.

The operating pressure of the coolant is 1 bar, which alsodefines the saturation temperature, which is 381 K. For theflow of coolant in the cooling jacket and flow of fresh air/exhaust air in the intake port/ exhaust port a typical flow andenergy boundary conditions are used, as described in Table 1.

Table 1. Flow and energy boundary conditions for thecylinder head boiling calculation

Figure 7, 8 and 9 show the results obtained on the coolingjacket wall using the boiling model presented in this paper.Figure 10 shows the temperature contours on the coolingjacket wall with single phase flow of liquid, withoutconsidering boiling.

Figure 7 shows the temperature contours on the coolingjacket wall. Temperature is high in the regions close to firedeck and exhaust port. Highest temperature is 415K, whichcorresponds to wall super heat of approximately 34K. Thistemperature is 45 K lower than that obtained with calculationwithout boiling, which is 460K as shown in Figure 10. Thusboiling lowers the maximum operating temperature of thecooling jacket significantly, which shows the advantage ofdeliberate use of boiling in the cooling jacket design.

Figure 8 shows the enhancement factor due to boiling, whichis defined as ratio of total heat transfer coefficient to singlephase heat transfer coefficient. A ratio of heat flux withboiling to that without boiling also results into a similarcontour plot. In the regions of significant boiling, this ratio isas high as six. In the regions without boiling, theenhancement factor has value of 1.

Figure 7. Temperature distribution of Cooling Jacketwall obtained from nucleate boiling simulation


Figure 8. Heat Transfer Enhancement Factor due tonucleate boiling

Figure 9. Volume fraction of vapor generated due tonucleate boiling

Figure 10. Temperature distribution from single phaseconjugate heat transfer analysis using same boundary

condition and heat flux profile

Figure 9 shows the vapor volume fraction in the domain.Maximum volume fraction reached for this case is 0.1, whichmeans the boiling regime is subcooled nucleate boiling.Again, regions of highest volume fraction are close to firedeck and exhaust port.

In Figure 9, high vapor volume fraction on the right uppercorner of the contour plot can be observed. This is a ridgelike portion of the cooling passage. Compering the sameregion with the upper contour plot in Figure 8, it can beconcluded that not all the region with high vapor volumefraction is undergoing boiling. Value of enhancement factorsuggests that only the lower part of the ridge has significantboiling. Since gravity is in negative z direction, vaporproduced at this lower part of the ridge moves upward due tobuoyancy and hence we see high vapor volume fraction in theupper part of this ridge. Thus stratification of vapor can beobserved.

In this case, vapor volume fraction is not very high. However,if vapor volume fraction approaches unity, we can concludethat a corresponding portion of the wall is covered withvapor, which reduces the local heat transfer rate significantly.In other words this also means that the total area available forheat transfer is reduced, which may result in increase ofoperating temperature of the system. Two phase flowsimulation along with wall boiling can help gain such insightof the flow.


Figure 11 shows heat flux is compared for the cases with andwithout boiling. When corresponding wall areas arecompared, higher heat fluxes are observed with boiling.

Figure 12 shows the fluid temperature in the cells in thevicinity of the coolant passage wall. When compared with thesingle phase calculation, it shows higher temperature withboiling in certain areas (A1), while lower temperature in theother (A2). Boiling results in higher heat fluxes near the walland the generated vapor mixes with the flow and condenses.This is an additional mechanism of heat transfer whichconsiderably changes the temperature map of the coolingjacket and cylinder head. This temperature map is the startingpoint for the thermal stress analysis of cooling jacket.

Figure 11. Total surface heat flux from Cooling Jacketwall (a) with boiling model (b) without boiling model

(single phase conjugate heat transfer)

Figure 12. Temperature of fluid in cell next to the wall(a) with boiling model (b) without boiling model (single

phase conjugate heat transfer)

CONCLUSIONSIn the present work, aCFD model is developed to simulatesubcooled nucleate flow boiling phenomenon that may occurin engine cooling jackets.

For validation, the model is used to predict the flow boilingof aqueous ethylene glycol over a flat sand casted roughplate, the conditions typically encountered in cooling jacketpassages. The simulation results show good comparison withthe experimental data, especially in terms of accuracy of thewall temperature, which an important parameter for enginecooling jacket analysis.

It is also shown that this model can be easily applied to a reallife cooling jacket geometry. In the example of cylinder headcooling jacket, vapor volume fraction was predicted up to10% and at certain locations; heat transfer enhancement up tosix times was obtained as compared to the single phase heattransfer. Important features of boiling like increase in heattransfer rate, reduction in operating temperature, vaporgeneration and stratification are captured, which provideinsight into the complex flow patterns of engine cooling


jacket. Temperature map of the cooling jacket is alsoobtained which is an important input for thermal stressanalysis. Thus the present boiling model can be very usefulfor cooling jacket design and optimization.

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CONTACT INFORMATIONAuthors can be contacted at following email addresses.

Hemant [email protected]

Saurish [email protected]

ACKNOWLEDGMENTSAuthors would like to thank Mr. Sourabh Shrivastava & Mr.Padmesh Mandloi ANSYS Inc. for providing simulationresults from the direct injection diesel engine study. Thanksare also extended to Dr. Laz Foley & Mr. Pranav Ladkat ofANSYS Inc. for their valuable inputs.

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