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Nanoscaled Particle Size Distributions and Gas Temperatures from Time-resolved LII Measurements

Nanoscaled Particle Size Distributions and Gas Temperatures from Time-resolved LII Measurements. H.Bockhorn, B.Jungfleisch, T. Lehre , R. Suntz. Institut für Chemische Technik and Engler-Bunte Institut Universität Karlsruhe. Motivation. Environmental: Soot emission regulations

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Nanoscaled Particle Size Distributions and Gas Temperatures from Time-resolved LII Measurements

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  1. Nanoscaled Particle Size Distributions and Gas Temperatures from Time-resolved LII Measurements H.Bockhorn, B.Jungfleisch, T. Lehre, R. Suntz Institut für Chemische Technik and Engler-Bunte Institut Universität Karlsruhe

  2. Motivation • Environmental: Soot emission regulations • Modelling: Data for gas-to-particle conversion models • Nanotechnology: Properties depend on p(r) • Product Design: Control p(r) by varying process parameters • Experimental approach : Optical method • Non-intrusive temporally and spatially resolved in-situ characterization of particle sizes

  3. , s = 0.34 Diameter D63 based on Present Particle Sizing Technique: RAYLIX Rayleigh-Scattering: 6th Moment M6 LII: 3th Moment M3

  4. Modelling LII: Mass and Energy Balances • Solving mass and engergy balance yields TP(t) • Accurate description of heat / mass transport kinetics is essential

  5. Modelling LII: Signal Decays Planck‘s law for a single particle: Signal decay for particle size distribution p(r): Assessment of p(r) and Tg:Multidimensional Nonlinear Regression yi: measured data y: model function si: weight

  6. Detection of Time-Resolved LII- Signals in laminar premixed flat flame (12kPa / 1 atm)

  7. LII Model validation TEM analysis yields: p(r) log-normal, s=0.34 2,6 nm < rm < 16 nm Na-D inversion method: gas temperatures Tg

  8. Comparison of measured and calculated LII-signals • Calculations agree with experiments (moderate laser fluxes) • Assessment of p(r) and Tg from LII signals seems possible

  9. Non-linear Regression: P(r) log-normal,  = 0.34; rm=8.3 nm; Tg=1724 K

  10. Excitation curves in atmospheric laminar premixed flat flame:Model and Measurements Model Uncertainties during LASER pulse due to Absorption kinetics Heat/mass transfer kinetics ???

  11. Particle Temperature Measurements : 2 colour LII

  12. 1D + time resolved 2 colour LII in laminar atmospheric premixed flat flame

  13. Additional Measurements in atmospheric laminar premixed flat flame Particle diameter: RAYLIX Flame temperature: 2 colour pyrometry

  14. Validation of heat/mass transfer kinetics Input to calculated T(t): measured TP(15ns after pulse); no absorption model p(r) and Tg from independant measurements

  15. Modelling LII during Laserpulsenot required Modelling superheatingnot required Independance of refractive index (grey bodies) Experimental value for laser fluencenot required Advantages of 2 colour LII

  16. monodisperse size distribution lognormal size distribution Nonlinear Regression Fit parameters: rm , s Fit function: TP(t) Result: Flat minimum regions = a rm + b

  17. Low time resolution has no effect on measured particle temperatures ( 2 colour LII ) for t > 20ns

  18. Nonlinear Regression: Fit parameters: rm , s Fit function: TP(20ns) –TP (1000ns) Unique minimum along s = a rm + b exists

  19. Sensitivity to rm for a given shape of p(r) lognormal s=0.34:rm = 5nm monodisperse: rm = 10nm

  20. Sensitivity of 2 colour LII to p(r)

  21. Particle Size Distributions from Scattering + LII Time-resolved LII: RAYLIX:

  22. space time Summary • LII model validation in sooting laminar premixed flames (1 bar; 0.12bar) • Heat/mass transfer kinetics validation based on particle temperature measurements • Assessment of p(r) and Tg from LII / 2 colour LII using Multi - D- nonlinear regression • Time range>1us gives good sensitivity to p(r) • Simultaneous detection of scattering increases sensitivity to p(r) • Outlook: P(r) in laminar diffusion flame

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