Vibrational spectroscopic monitoring of CO2-O energy transfer: cooling processes in atmospheres of Venus & Mars

The vibrational excitation of CO2 by a fast-moving O atom followed by infrared emission from the vibrationally excited CO2 has been shown to be an important cooling mechanism in the upper atmospheresof Venus, Earth and Mars. We are trying to determine more precisely the efficiency (rate coefficient) of the CO2-O vibrational energy transfer. For experimental ease the reverse reaction is used, i.e. collision of a vibrationally excited CO2 with atomic O, where we are able to convert to the atmospherically relevant reaction via a known equilibrium constant. The goal of this experiment was to measure the magnitudes of rate coefficients for vibrational energy states above the first excited state, a bending mode in CO2. An isotope of CO2, 13CO2, was used for experimental ease. The rate coefficients for given vibrational energy transfers in 13CO2 are not significantly different from 12CO2 at this level of precision. A slow-flowing gas mixture was flowed through a reaction cell: 13CO2 (vibrational specie of interest), O3(atomic O source), and Ar (bath gas). Transient diode laser absorption spectroscopy was used to monitor thechanging absorption of certain vibrational modes of 13CO2 after a UV pulse from a Nd:YAG laser was fired. Ozone absorbed the UV pulse in a process which vibrationally excited 13CO2 and liberated atomic O.Transient absorption signals were obtained by tuning the diode laser frequency to an appropriate ν3 transition and monitoring the population as a function of time following the Nd:YAG pulse. Transient absorption curves were obtained for various O atom concentrations to determine the rate coefficient of interest. Therotational states of the transitions used for detection were difficult to identify, though their short reequilibration timescale made the identification irrelevant for vibrational energy transfer measurements. The rate coefficient for quenching of the (1000) state was found to be (4 ± 8) x 10-12 cm3 s-1 which is the same order of magnitude as the lowest-energy bend-excited mode: (1.8 ± 0.3) x 10-12 cm3 s-1. More data is necessary before it can be certain that the numerical difference between the two is real.

Vibrational Relaxation of N2O (v2) by Atomic Oxygen Measured by Tunable Diode Laser Absorption Spectroscopy

Through the use of Transient Diode Laser Absorption Spectroscopy (TDLAS), the rate coefficient for the vibrational relaxation of N2O (ν2) by O(3P) at room temperature (32 ºC)) was determined to be (1.51 ± 0.11)x10-12 cm3molecule-1sec-1. A Q-switched, frequency quadrupled (266 nm) Nd:YAG laser pulse was used as the pump for this experiment. This pulse caused the photodissociation of O3 into O2 and O atoms.Excited oxygen (O(1D)) was collisionally quenched to ground state (O(3P)) by Ar and/or Xe. Photodissociation also caused a temperature jump within the system, exciting the ν2 state of N2O molecules. Population in the ν2 state was monitored through a TDLASobservation of a ν3 transition. Data were fit using a Visual Fortran 6.0 Global Fitting program. Analysis of room temperature data taken using only Ar to quench O atoms to the ground state gave the same rate coefficient as analysis of data taken using an Ar/Xe mixture, suggesting Ar alone is a sufficient bath gas. Experimentation was alsoperformed at -27 ºC and -82 ºC for a temperature dependence analysis. A linear regression analysis gave a rate coefficient dependence on temperature of ... for the rate coefficient of the vibrational relaxation of N2O (ν2) by atomic oxygen.

Development of Dynamic Constraint Models for a Model Based Transient Calibration Process

Model based calibration has gained popularity in recent years as a method to optimize increasingly complex engine systems. However virtually all model based techniques are applied to steady state calibration. Transient calibration is by and large an emerging technology. An important piece of any transient calibration process is the ability to constrain the optimizer to treat the problem as a dynamic one and not as a quasi-static process. The optimized air-handling parameters corresponding to any instant of time must be achievable in a transient sense; this in turn depends on the trajectory of the same parameters over previous time instances. In this work dynamic constraint models have been proposed to translate commanded to actually achieved air-handling parameters. These models enable the optimization to be realistic in a transient sense. The air handling system has been treated as a linear second order system with PD control. Parameters for this second order system have been extracted from real transient data. The model has been shown to be the best choice relative to a list of appropriate candidates such as neural networks and first order models. The selected second order model was used in conjunction with transient emission models to predict emissions over the FTP cycle. It has been shown that emission predictions based on air-handing parameters predicted by the dynamic constraint model do not differ significantly from corresponding emissions based on measured air-handling parameters.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

Reduction of Transient Particulate Matter Spikes with Decision Tree Based Control

Decision trees have been proposed as a basis for modifying table based injection to reduce transient particulate spikes during the turbocharger lag period. It has been shown that decision trees can detect particulate spikes in real time. In well calibrated electronically controlled diesel engines these spikes are narrow and are encompassed by a wider NOx spike. Decision trees have been shown to pinpoint the exact location of measured opacity spikes in real time thus enabling targeted PM reduction with near zero NOx penalty. A calibrated dimensional model has been used to demonstrate the possible reduction of particulate matter with targeted injection pressure pulses. Post injection strategy optimized for near stoichiometric combustion has been shown to provide additional benefits. Empirical models have been used to calculate emission tradeoffs over the entire FTP cycle. An empirical model based transient calibration has been used to demonstrate that such targeted transient modifiers are more beneficial at lower engine-out NOx levels.

Vibrational Relaxation of 13CO2(v2) by Atomic Oxygen

Carbon dioxide (CO2) has been of recent interest due to the issue of greenhouse cooling in the upper atmosphere by species such as CO2 and NO. In the Earth’s upper atmosphere, between altitudes of 75 and 110 km, a collisional energy exchange occurs between CO2 and atomic oxygen, which promotes a population of ground state CO2 to the bend excited state. The relaxation of CO2 following this excitation is characterized by spontaneous emission of 15-μm. Most of this energy is emitted away from Earth. Due to the low density in the upper atmosphere, most of this energy is not reabsorbed and thus escapes into space, leading to a local cooling effect in the upper atmosphere. To determine the efficiency of the CO2- O atom collisional energy exchange, transient diode laser absorption spectroscopy was used to monitor the population of the first vibrationally excited state, 13CO2(0110) or ν2, as a function of time. The rate coefficient, kO(ν2), for the vibrational relaxation 13CO2 (ν2)-O was determined by fitting laboratory measurements using a home-written linear least squares algorithm. The rate coefficient, kO(ν2), of the vibrational relaxation of 13CO2(ν2), by atomic oxygen at room temperature was determined to be (1.6 ± 0.3 x 10-12 cm3 s-1), which is within the uncertainty of the rate coefficient previously found in this group for 12CO2(ν2) relaxation. The cold temperature kO(ν2) values were determined to be: (2.1 ± 0.8) x 10-12 cm3 s-1 at Tfinal = 274 K, (1.8 ± 0.3) x 10-12 cm3 s-1 at Tfinal = 239 K, (2 ± 1) x 10-12 cm3 s-1 at Tfinal = 208 K, and (1.7 ± 0.3) x 10-12 cm3 s-1 at Tfinal = 186 K. These data did not show a definitive negative temperature dependence comparable to that found for 12CO2 previously.

Product Distributions Following Hyperthermal Collisions Between C2H4 And O(3P)

Transient Diode Laser Absorption Spectroscopy (TDLAS) was used to perform vibrational state population studies of the CO2 product from the hyperthermal reaction between C2H4 and O(3P) at room temperature using O3 as the O-atom precursor. Photodissociation of O3 using a frequency quadrupled Q-switch Nd:YAG laser pulse at 266 nm produced O(3P) atoms at high velocities which subsequently reacted with C2H4, producing several primary and secondary products including CO2. The CO2 product was detected using high-resolution TDLAS under five unique sets of reaction conditions. The vibrational distribution of the CO2 product did not follow a Boltzmann distribution at all five sets of conditions. The experiments showed a distribution in which there was a surprisingly high population in the (1000) (symmetric stretching) state compared with the other states probed, all of which contained bend excitation. In general, the CO2 population in the (1000) state was about 15-20% more populated than the Boltzmann distribution predicts. A possible explanation for this result may lie in the mechanism of CO2 evolution from the C2H4 + O(3P) reaction.

Analysis and Prediction of Transient Opacity Spikes Using Dimensional Modeling

Dimensional modeling, GT-Power in particular, has been used for two related purposes-to quantify and understand the inaccuracies of transient engine flow estimates that cause transient smoke spikes and to improve empirical models of opacity or particulate matter used for engine calibration. It has been proposed by dimensional modeling that exhaust gas recirculation flow rate was significantly underestimated and volumetric efficiency was overestimated by the electronic control module during the turbocharger lag period of an electronically controlled heavy duty diesel engine. Factoring in cylinder-to-cylinder variation, it has been shown that the electronic control module estimated fuel-Oxygen ratio was lower than actual by up to 35% during the turbocharger lag period but within 2% of actual elsewhere, thus hindering fuel-Oxygen ratio limit-based smoke control. The dimensional modeling of transient flow was enabled with a new method of simulating transient data in which the manifold pressures and exhaust gas recirculation system flow resistance, characterized as a function of exhaust gas recirculation valve position at each measured transient data point, were replicated by quasi-static or transient simulation to predict engine flows. Dimensional modeling was also used to transform the engine operating parameter model input space to a more fundamental lower dimensional space so that a nearest neighbor approach could be used to predict smoke emissions. This new approach, intended for engine calibration and control modeling, was termed the "nonparametric reduced dimensionality" approach. It was used to predict federal test procedure cumulative particulate matter within 7% of measured value, based solely on steady-state training data. Very little correlation between the model inputs in the transformed space was observed as compared to the engine operating parameter space. This more uniform, smaller, shrunken model input space might explain how the nonparametric reduced dimensionality approach model could successfully predict federal test procedure emissions when roughly 40% of all transient points were classified as outliers as per the steady-state training data.

Vibrational Relaxation of O3(nu2) by O((3)P)

Laboratory measurements of the rate coefficient for quenching of O3(nu2) by ground-state atomic oxygen, kO(nu2), at room temperature are presented. kO(nu2) is currently not well known and is necessary for appropriate nonlocal thermodynamic equilibrium modeling of the upper mesosphere and lower thermosphere. In this work, a 266 nm laser pulse photolyzes a small amount of O3 in a slow-flowing gas mixture of O3, Xe, and Ar. This process simultaneously produces atomic oxygen and increases the temperature of the gas mixture slightly, thereby increasing the population in the O3(nu2) state. Transient diode laser absorption spectroscopy is used to monitor the populations of the O3(nu2) and ground vibrational states as the system re-equilibrates. Relaxation rates are measured over a range of quencher concentrations to extract the rate coefficient of interest. The value of kO(nu2) was determined to be (2.2 0.5) * 10(-12) cm(3) s(-1).