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ICAT, November 13-14 2008. Outline Background, motivation and goals Kinetic Models Validation against shock tube experiments Comparison against HCCI experiments.

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Presentation on theme: "ICAT, November 13-14 2008. Outline Background, motivation and goals Kinetic Models Validation against shock tube experiments Comparison against HCCI experiments."— Presentation transcript:

1 ICAT, November 13-14 2008

2 Outline Background, motivation and goals Kinetic Models Validation against shock tube experiments Comparison against HCCI experiments with PRFs Conclusions

3 Background and problem statement Mechanisms for pollutant formation and ignition characteristics need to be compact for integration with complex fluid flow calculations Reduced chemistry for: Variable components of fuel mixtures, Varying conditions. is necessary for HCCI simulations and development.

4 Conflict between chemical and physical complexity Chemical Information in Combustion Calculations Multi-D flow model Max 100 reactions Simple fuels Homogeneous model ~1000 reactions Practical fuel mixtures Great span between high/low values, slow/fast processes: stiffness  additional numerical problems 3D flow calculation: ~10 6 computational cells Turbulent flow:~10 1 differential equations for independent variables Detailed Chemistry: ~10 2 extra differential equations

5 Kinetic Models  The detailed mechanism : The latest reaction mechanism for PRFs from the LLNL 4238 reactions and 1034 species, most of them reversible. The detailed mechanism has been developed for wide range of engine applications.  The skeletal mechanism : 386 reactions and 63 species. The skeletal mechanism has been developed for SI knocking conditions by using an automatic reduction method. Here both mechanisms will be validated for HCCI conditions by using shock tube and real engine experiments

6 Measure- ment Fitting to measurements Pro: Compact and reliable Con: Restricted range of conditions Equipment intensive Easily measurable species only Methods for reducing mechanisms Fitted mechanism Detailed mechanism Systematic reduction Skeletal mechanism Pro: Versatility of detailed mechanism Standard procedure for recalculation Automation possibility Con: Expertise and labour intensive

7 The automatic reduction method: Sensitivity and reaction flow analyses Removal of redundant reaction paths A measure of redundance: Reaction flow - transfer rate of atomic species between molecules

8 Species sensitivity analysis and necessity index A species with low reaction flow is not necessarily redundant! Influence on important combustion parameters has to be measured Sensitivity and reaction flow in one: species necessity c A,E A B C D E f E,A

9 Conditions and parameter ranges Two intake conditions are compared; (i)high intake temperature and low intake pressure (ii) low intake temperature and high intake pressure Experimental data for PRF 94 and PRF 84: Andrae, Johansson, Björnbom, Risberg, Kalghatgi, Combust. Flame, 140:267-86, (2005).

10 Model validation against shock tube ignition delay times from Fieweger.

11 Isooctane validation against shock tube ignition delay times T5KT5K p 5 atm Experiment t i / ms LLNL t i / ms Rel.Err. % Skeletal t i / ms Rel.Err. % 85556.41719 311881% 195113% 86759.31755 276257% 1711-3% 89458.51193 2460106% 158032% 92755.71067 189778% 141132% 97551.2871 107023% 9509% 98418.11511 256270% 225049% 99516.31535 246060% 207335% 100651.1625 69010% 6341% 101547.8505 65029% 60019% 104317.1927 129139% 10099% 107718.4604 80433% 6243% 109847.5222 2314% 219-1% 110915.9516 64725% 501-3% 115914.9214 37475% 33054%

12 n-heptane validation against shock tube ignition delay times T5KT5K p 5 atm Experiment t i / ms LLNL t i / ms Rel.Err. % Skeletal t i / ms Rel.Err. % 80620.01.381.17 -15% 1.08-22% 85019.91.651.29 -22% 1.34-19% 90619.81.842.30 25% 2.4936% 90953.90.250.36 42% 0.25-2% 92360.00.240.32 32% 0.22-10% 92660.60.230.32 38% 0.21-10% 93255.40.320.39 21% 0.27-16% 98548.60.360.70 92% 0.4215% 100757.70.230.53 128% 0.2925% 101218.10.942.14 127% 1.2735% 101353.60.290.58 99% 0.329% 102354.20.260.54 108% 0.2911% 102759.10.240.47 99% 0.255% 104816.70.851.49 75% 0.83-3% 105750.00.190.45 131% 0.2424% 106353.10.180.39 118% 0.2117% 111552.30.100.22 117% 0.1327%

13 Comparison against HCCI experiments with PRFs Experimental [27] and calculated pressures for PRF 84 in a HCCI Engine: p o =1.0 bar, T o =393 K, f = 0.2857, Engine speed = 900 rpm, e = 16.7, V d =1.95 dm 3. Calculations start at -99 degrees ATDC at 472 K and 1.74 bar [28].

14 Experimental [27] and calculated pressures for PRF 94 in a HCCI Engine: po=1.0 bar, To=393 K, f = 0.2857, Engine speed = 900 rpm, e = 16.7, Vd =1.95 dm3. Calculations start at -99 degrees ATDC at 455 K and 1.37 bar [28].

15 Experimental [27] and calculated pressures for PRF 84 in a HCCI Engine. po=2.0 bar, To=313 K, f = 0.25, Engine speed = 900 rpm, e = 16.7, Vd = 1.95 dm3. Calculations start at -99 degrees ATDC at 415 K and 3.34 bar [28].

16 Experimental [27] and calculated pressures for PRF 94 in a HCCI Engine. po=2.0 bar, To=313 K, f = 0.25, Engine speed = 900 rpm, e = 16.7, Vd = 1.95 dm3. Calculations start at -99 degrees ATDC at 415 K and 3.34 bar [28].

17 CPU time was found to decrease two orders of magnitude when using the skeletal mechanism compared to the detailed one. Computational Gain

18 possibility for further reduction QSSA ONLINE REDUCTION …….

19 Species lifetimes and reduction by QSSA Species lifetime from Jacobian of chemical source terms: A fast reversible reaction with a short-lived species CH 3 + OH  CH 3 O + H An explicit algebraic expression (which is easily calculated) => the species can be removed from the set of differential equations: Quasi Steady-State Assumption (QSSA):

20 Software Chain Detailed mechanism (data) Skeletal mechanism (data) Reaction flow and sensitivity analysis Range of test calculations (simplified model) Removal of redundant reactions Reduced mechanism (code) CFD code (PDF, RIF) Quasi steady-state approximations (QSSA) Chemical and physical lifetime plus sensitivity analysis Range of test calculations (simplified model) State variables and major concentrations Source terms

21 Detailed mechanism (data) Skeletal mechanism (data) Software Chain Reduced mechanism (code)

22 Reaction flow and sensitivity analysis Range of test calculations (two-zone model) Removal of redundant reactions

23 Range of test calculations (two-zone model) Chemical and physical lifetime plus sensitivity analysis Quasi steady-state approximations (QSSA)

24 CFD code (PDF, RIF) State variables and major concentrations Source terms

25 Summary and conclusions A method for automatic reduction of detailed reaction mechanisms has been developed and tested with a two-zone model for knocking combustion in an SI engine fuelled with PRF. Reaction flow, species sensitivity and lifetime analysis were calculated for a whole range of engine operating characteristics and used for ranking species by importance. The detailed mechanism was reduced to a skeletal one with 62 species, yielding <0.25 CAD error in ignition delay. The skeletal mechanism was in turn reduced to 17 species by QSSA, with an ignition delay error of <1 CAD. The observed errors increase monotonously with increasing degree of reduction, indicating the relevance of the ranking measures

26 Summary and conclusions Error occurring by using the smaller mechanisms may be larger compared to detailed mechanisms in wide range, but it would be reduced dramatically for specified problems. The detailed mechanism: generated to model precisely fuel oxidation and autoignition over a large range in chemical features, includes several hundred of species and several thousand of reactions. their usage in multi-dimensional simulations is not possible. The skeletal mechanism: the skeletal mechanism have been successfully validated to experimental data for isooctane, n- heptane and mixtures of the two fuels obtained from shock tube experiments skeletal mechanism reduces the computational difficulties and the CPU time during the multi- dimensional simulations. Here CPU time was found to decrease two orders of magnitude when using the skeletal mechanism compared to the detailed one. skeletal mechanism gives good agreement with experimental results. skeletal mechanism can be used in engine simulations within the range of the validation for future efforts in the field of HCCI combustion and engine development.

27 Acknowledgements The authors would like to acknowledge financial support from: Shell Global Solutions (UK), Chester, United Kingdom European Community (EC), FP6 Marie Curie Program This work has been financed under the European Commission Marie Curie Transfer of Knowledge Scheme (FP6) pursuant to Contract MTKI-CT-2004-509777 and was performed within a framework of a research and technological development program with the title SUSTAINABLE FUELUBE.

28 Thanks for your attention. I would like to invite you to International Conference on Fuels and Combustion in Engines in Istanbul, September 2009 For more information fce@sakarya.edu.tr www.fce.sakarya.edu.tr

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