Combustion of the Butanol Isomers: Reaction Pathways at Elevated Pressures from Low-to-High Temperatures The Context & Challenge Goals/Philosophy of this Work Our Model Development Process Summary
Pyrek, Kelly, Medical Group Editor has reference to this Academic Journal, PHwiki organized this Journal Combustion of the Butanol Isomers: Reaction Pathways at Elevated Pressures from Low-to-High Temperatures Michael R. Harper, Mary Schnoor, Shamel Merchant, William H. Green, Kevin M. Van Geem, Bryan W. Weber, Chih-Jen Sung, Ivo Stranic, David F. Davidson, in addition to Ronald K. Hanson MIT, U.Ghent, U.Conn., & Stan as long as d Primary Source of Funding: US DOE Combustion Energy Frontier Research Center The Context & Challenge World is running out of light sweet crude in addition to benefits to using biofuels instead Dozens of alternative fuels proposed, how to assess which are worth pursuing Several new combustion concepts, how to assess how they work with future fuels Increasing regulation of emission species need models with more chemistry Goals/Philosophy of this Work Improve capability to predict per as long as mance of proposed new fuels Faster, cheaper than exptlly testing all fuels Butanol as a test case Can we build accurate models quickly How Accuracy of predictions How to validate models Right answers as long as the Right Reasons: true rate coefficients, dont as long as ce fits
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Very Big Models: Need to Think Differently So many possible reactions in addition to species! Select ~350 species from ~30,000 considered. Select ~7,000 reactions from ~106 considered. No way to determine all the numbers in the model experimentally in addition to impractical to compute them all accurately. Most experiments do not conclusively determine any number, instead constrain some combination. Fuel per as long as mance in addition to experiments are not sensitive to most of these numbers if those numbers are right order of magnitude Different experiments sensitive to different subsets of species in addition to reactions. Our Model Development Process Computer assembles large kinetic model as long as particular condition(s) using rough estimates of rate coefficients. (open source RMG software) Start from model derived as long as other conditions, so appending new reactions in addition to species. Automated identification of chemically activated product channels, in addition to computation of k(T,P). If sensitive to k derived from rough guess, recompute that k using quantum chemistry. Generalize from quantum to improve rate rules. Iterate until not sensitive to rough estimates. Compare with experiment. Big discrepancies Look as long as bugs or typos. Match OK Repeat as long as different conditions. Many Experimental Data on Butanol Combustion/Oxidation/Pyrolysis Ignition Delays Shock tube Rapid compression machine (see poster T40) Flame Speeds spherical in addition to flat flames Speciated Data from: MS sampling in premixed in addition to diffusion flames Flow reactors (pyrolysis & oxidation) Jet-Stirred Reactors Rapid Compression Facility Next talk: Species time profiles in shock tube We test our butanols model against all these types of experiments
Pyrolysis of the butanol isomers was conducted at the Laboratory as long as Chemical Technology (Ghent) 1: butanol vessel, 2: water vessel, 3: electronic balance, 4: pump, 5: valve, 6: evaporator, 7: mixer, 8: heater, 9: air, 10: pressure regulator, 11: mass flow controller, 12: nitrogen, 13: reactor, 14: nitrogen internal st in addition to ard, 15: oven, 16: GC as long as as long as maldehyde in addition to water, 17: GC as long as C5+, 18: cyclone, 19: condenser, 20: dehydrator, 21: GC as long as C4-, 22: data acquisition The kinetic models predicted conversion agrees very well with the experimental pyrolysis measurements The kinetic model also predicts the pyrolysis product distribution well, including benzene in addition to small aromatics
Advanced Light Source allows direct detection of dozens of species including key radicals Photoionization Molecular Beam Mass Spectrometry Flames are analyzed with molecular beam time-of-flight mass spectrometry Photoionization with tunable synchrotron-generated VUV photons allows identification of species by mass by ionization energy Experimental mole fraction profiles are compared with flame model predictions in addition to reaction path in addition to sensitivity analysis are per as long as med Advanced Light Source (ALS) Flame Data: Detailed Test of the Models Predictive Capabilities Hansen, Harper,Green PCCP (submitted) Mole fraction profiles of the major species are predicted accurately A more powerful test is provided by comparing modeled in addition to experimental profiles of intermediate species Profiles have not been shifted Oßwald et al. flame data need to be shifted as long as better agreement Only a few of the many data traces shown here most show good agreement Oßwald, Güldenberg, Kohse-Höinghaus, Yang, Yuan, Qi, Combust.Flame (2011)158, 2 You learn more from discrepancies! C4H4 in addition to C3H3 overpredicted Sensitive to C4H5 Thermochemistry Simulations of the flames studied by ALS are sensitive to the enthalpy of as long as mation of i-C4H5 (CH2=CH-C=CH2 CH2-CH=C=CH2) . None of the other available experimental data are sensitive to this number. This radicals enthalpy value was incorrect in the MIT database. Correcting to the accepted literature value largely resolved the discrepancy. Now investigating origins of smaller discrepancies
Focus on what is important! Most important fuel per as long as mance property: ignition delay Gasoline Octane Number Diesel Cetane Number Small changes in fuel make big changes in ignition: sensitive to molecular structure! New engines under development are even more sensitive to ignition Potential as long as big gains but only if the fuel ignition delay time matches engine requirements Model fairly accurate as long as high-T ignition delays As we replace rough estimates with ks from quantum, accuracy gradually improves. Experiments: Stan as long as d US meeting= MIT model 4 months ago
Practical Engine Ignition: High Pressure in addition to Low Temperature n-butanol ignition is much faster than the other butanol isomers as long as T< 900 K Measured by Bryan Weber & C.J. Sung (U.Conn.). Poster T40 Big Discrepancy: Model did not predict fast n-butanol ignition observed at T<900 K! Model was built automatically using computer expert system Due to mistake in rate database used by expert system, model wildly mis-estimated barrier as long as HO2 + C-H reactions. With reasonable k as long as HO2 + butanol, model predicts ignition delay down to 800 K at 15 atm Model was built automatically at MIT using computer expert system Due to mistake in rate database used by expert system, model wildly mis-estimated barrier as long as HO2 + C-H reactions. After correcting that big mistake, current CEFRC model is much closer but still not quite right at low T, high P. Work continues Model not capturing dependence on [O2] below 800 K: probably missing or mis-estimating some peroxyl chemistry Exptl Data: U.Conn. MIT model Predictions Sensitive to chemically-activated R+O2 = QOOH: g-C4H8OH + O2 (+M) = CH3CH(OOH)CH2CHOH Summary Kinetic models based on quantum chemistry + rate estimates can be predictive as long as huge range of combustion/oxidation/pyrolysis experiments. Big models can be built in addition to refined pretty quickly. Experimentalists + Modelers team very effective. Useful as long as assessing proposed new fuels Big errors usually due to bugs, typos, holes in database. Experiments in addition to team-mates great as long as catching them! P-dependence in addition to chemical activation important as long as high-T, but also in peroxyl chemistry. More than 50% of ks in model are significantly P-dependent. Starting to reach expected factor of 2 small errors due to inaccuracies in rate coefficients in addition to thermo. May be difficult to significantly improve accuracy but calculations can be great guide as long as experiments to more precisely determine key parameters. Kinetics is starting to become a predictive science, possible to use in predictive design of new processes.
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