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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Reduced Models for Chemical Kinetics derived from Parallel Ensemble Simulations of Stirred Reactors

Detailed chemical kinetic models are essential to improve the predictive capability of computational fluid dynamics (CFD) simulations and to impact the development of next generation combustion technologies. However, such detailed kinetic models are beyond the reach of CFD codes due to the computational cost of transporting additional chemical degrees of freedom. Reduced order models for combustion kinetics exploit the presence of lower dimensional manifolds in the state space and require far fewer number of scalars to be transported as part of CFD simulations. In this paper, we describe the software infrastructure developed to allow large ensembles of stirred reactor configurations with detailed chemical kinetics. The canonical reactor simulations are incorporated in a workflow with sparse grid and data reduction methodologies aimed at development of reduced order models. We present results from analyzing the results of the stirred reactor calculations for syngas mixture using principal component analysis (PCA) and neural network methodologies. The results show that nonlinear autoencoder model can surpass PCA in representing the original dataset with far fewer degrees of freedom.

Zhang, Pei↗
DOE OSTI2023

Reduced chemical kinetic model for CH 4 -air non-premixed flames including excited and charged species

Electric fields can impact small laminar flames by changing their shape and overall behavior by acting on charged species produced in combustion. However, no reduced chemical kinetic model has been developed considering both major species and minor species related to flame characterization and flame behavior in the presence of an electric field. Here, this study presents a reduced chemical kinetic model for methane-air combustion which includes minor excited species (CH*and OH*) and charged species (H 3 O + , HCO + , C 2 H 3 O + , CH 5 O + , O$_{2}^{–}$, OH – , e – , CO$_{3}^{–}$, CHO$_{2}^{–}$, O – , CHO$_{3}^{–}$). The results employing the reduced chemistry model have been validated for a two-dimensional flame geometry by comparison with (i) detailed chemistry simulation results for species location and peak values, and (ii) experimental CH* chemiluminescence location, considering the self-repulsion of charges yet without externally applied electric field to the flame. This reduced chemical kinetic model, with 45 species and 216 reactions, shows a computational demand one-third that of employing its equivalent detailed chemistry (83 species and 394 reactions). The reduction is modest but significant considering that high fidelity is needed to capture the behavior of the chemi-ion and chemiluminescent species. Future works will involve the use of this model for simulations predicting flame behavior with applied electric field (i.e., field strength ≠0 kV/cm).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Chemical kinetic interactions and sensitivity analyses for 2-ethylhexyl nitrate-doped PRF91 using a reduced mechanism

A numerical and experimental investigation about the chemical kinetic interactions between 2-ethylhexylnitrate (EHN) and PRF91 was performed in this study. Rapid compression machine experiments were conducted to investigate the effect of EHN on the autoignition reactivity of the fuel, and a reduced chemical kinetic mechanism was developed including an EHN sub-model. Experiments showed that the ignition delay decreases as the fuel is doped with EHN, but the effect of the doping level of EHN on the ignition is highly non-linear. Moreover, experiments showed that the EHN effectiveness is lowest during the transition between the low-temperature regime and the negative temperature coefficient (NTC) regime, and it rapidly increases as the temperature increases. Both detailed and (developed) reduced mechanisms were validated against the experimental results, allowing a more in-depth EHN-fuel chemistry study. Additionally, ignition delay sensitivity and EHN effectiveness sensitivity analyses were performed with the reduced mechanism to identify the reactions that control the interaction between EHN and the fuel. As the result, EHN thermal decomposition is only relevant for very low temperatures. The chemistry of EHN-doped fuel is more sensitive to intermediate temperature reactions than that of straight fuel, especially at lower temperatures, due to the effect of EHN on the NTC behavior of the fuel. Finally, the chemistry of EHN-doped fuel is very sensitive to NO 2 -to-NO reactions, especially at high temperatures, because these reactions transform the NO 2 generated by EHN into NO, which is a very effective fuel reactivity enhancer.

2-ethylhexyl nitrate↗
DOE OSTI2026

Predictive Chemical Kinetic Modeling: Where We Succeed, Where We Struggle, and What Comes Next

Chemical kinetic modeling plays a foundational role in fields ranging from energy to environmental science, pharmaceuticals, and advanced materials. The past two decades have seen remarkable progress, particularly in modeling gas-phase reactions for thermochemical processes, leading to impactful industrial applications such as steam cracking and air quality management. However, new challenges are emerging. The successful development of systematic methodologies for the description of gas-phase kinetics opens the possibility to apply the same approach to the study of more challenging systems. Here, we review recent advances, including ab initio transition state theory-based master equation estimation of elementary rates, automated mechanism generation, machine-learning-assisted kinetics, and uncertainty quantification, and discuss the advances needed to apply the same methodological approach in areas such as heterogeneous catalysis, electrochemistry, liquid-phase and solid-state reactivity, and multiscale model integration. We advocate for the development of targeted tools, especially methods that go beyond empirical tuning toward first-principles-based predictions. We highlight the need for accessible software and AIaugmented workflows to democratize modeling for industry and academia alike. In this perspective, we call attention to not only what has worked but also what remains unsolved, advocating to avoid overemphasizing successes in scientific works at the expense of realism. The next decade should focus on predictive capability, physical accuracy, and community infrastructure (e.g., databases and services) to enable innovation across diverse fields. We argue that kinetic modeling, properly equipped, can accelerate discovery far beyond its traditional domains.

ab initio calculations↗
DOE OSTI2022

Chemical kinetic interactions of NO with a multi-component gasoline surrogate: Experiments and modeling

Here this work reports an experimental and modeling study on the chemical kinetic interactions of NO with a multi-component gasoline surrogate, namely PACE-20, using a twin-piston rapid compression machine at a stochiometric fuel loading with 20% EGR (exhaust gas recirculation) by mass, pressures of 20 and 40 bar, and temperatures from 700 to 930 K. Five NO concentrations are investigated, namely 0, 20, 50, 70 and 150 ppm, where NO addition effects are characterized through changes in PACE-20 ignition reactivity and heat release characteristics. Experiments indicate that within the low-temperature regime, NO promotes low-temperature heat release rate and main ignition reactivity at low addition levels, with saturation or even inhibiting effects observed at >50 ppm NO addition, while within the NTC/intermediate-temperature regime, adding NO only promotes reactivity. A recently updated, detailed chemical kinetic model with chemistry specific to NOx/hydrocarbons interaction incorporated is used to simulate the experiments, and reasonable agreement is obtained. In-depth sensitivity and rate of production analyses are further performed. The results indicate that NO interacts with PACE-20 via two types of interaction: (a) direct interactions between NO and PACE-20 derivatives, primarily through NO+HO 2 ↔NO 2 +OH and RO 2 +NO↔RO+NO 2 , and (b) indirect interactions between PACE-20 derivatives and NO 2 produced from the direct interactions, primarily through R+NO 2 ↔RO+NO. The observed NO inhibiting effect at low temperatures and 150 ppm NO addition is attributed to the lack of HO 2 radicals to sustain NO consumption via NO+HO 2 ↔NO 2 +OH, and the take-up of inhibiting pathways via RO 2 +NO↔RO+NO 2 . The results also indicate that even with the presence of multiple fuel components, NOx/hydrocarbons interactions are highly selective, and are mainly initiated by the interactions between NO and RO 2 radicals from cyclopentane and ethanol, as well as between NO 2 and R radicals from toluene, 1,2,4-trimethylbenzene and 1-hexene. Further studies on these interactive reactions are therefore highly recommended.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Probabilistic effects of porosity and chemical kinetics on the shock initiation of an octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) based explosive

In this work, we investigate the effects of porosity and chemical reactivity on the shock initiation of an HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine)-based polymer bonded explosive due to thin flyer impact using two-dimensional mesoscale simulations. Microstructural samples are computationally generated, and the calculated shock response is compared to experiments. The sample dimensions are 0.1×1.05 mm 2 , and each sample accounts for grain scale heterogeneities, including randomized grain morphology and pore spacing. Simulations are performed using the Lawrence Livermore National Laboratory (LLNL) arbitrary Lagrangian–Eulerian multi-physics code ALE3D. Chemistry and equation of states are handled with LLNL's thermochemical code Cheetah. We employ a modified Arrhenius-based chemical kinetics model that scales the temperature exponent fitting parameter with flyer shock conditions. This new model is calibrated to the mean response of experimental shock initiation thresholds for three separate Kapton flyer thicknesses. A simplified shock initiation criterion is proposed, which classifies the macroscale initiation response based on cross-sectional temperature profiles of the shocked sample. This criterion is used to further investigate the probabilistic response of the sample to variations in the mean porosity and chemical kinetics rate, and we find an inverse correlation between the shock pressure and the confidence interval of the experimental threshold velocity. Furthermore, the methodology presented in this work for quantifying the probabilistic nature of shock initiation is material agnostic. These mesoscale studies may be used to inform continuum scale models and expedite the development of future, tailored energetic formulations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

CSPlib - A Software Toolkit for the Analysis of Dynamical Systems and Chemical Kinetic Models

CSPlib is an open source software library for analyzing general ordinary differential equation (ODE) systems and detailed chemical kinetic ODE systems. It relies on the computational singular perturbation (CSP) method for the analysis of these systems. The software provides support for: General ODE models (gODE model class) for computing source terms and Jacobians for a generic ODE system; TChem model (ChemElemODETChem model class) for computing source term, Jacobian, other necessary chemical reaction data, as well as the rates of progress for a homogenous batch reactor using an elementary step detailed chemical kinetic reaction mechanism. This class relies on the TChem [2] library; A set of functions to compute essential elements of CSP analysis (Kernel class). This includes computations of the eigensolution of the Jacobian matrix, CSP basis vectors and co-vectors, time scales (reciprocals of the magnitudes of the Jacobian eigenvalues), mode amplitudes, CSP pointers, and the number of exhausted modes. This class relies on the Tines library; A set of functions to compute the eigensolution of the Jacobian matrix using Tines library GPU eigensolver; A set of functions to compute CSP indices (Index Class). This includes participation indices and both slow and fast importance indices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Flame Chemistry Workshop: a perspective on challenges and strategic actions in combustion experiments and chemical kinetics modeling

Continued progress in the development of predictive models for combustion chemistry—including ignition and flame behavior, species evolution, and combustion system performance—relies on overcoming enduring and emerging challenges in experimental measurements, theoretical formulations, and chemical kinetics mechanism construction. As combustion science continues to coincide with advances in sustainable fuels development, plasma technologies, and automated modeling capabilities, the need for coordinated, community-driven strategies is essential. The Flame Chemistry Workshop (FCWS), held biennially before the International Symposium on Combustion, serves as a dedicated platform to identify, consolidate, and address these challenges in a structured and collaborative manner. This perspective arises from discussions at the 7th FCWS in Milan, Italy (2024), and presents a collective view of the critical barriers currently limiting progress. Across the five technical domains discussed during the 7th FCWS – sustainable fuels combustion, advanced diagnostics for combustion measurements, experiments and modeling in plasma combustion, artificial intelligence and automated methods for theory and mechanisms generation, and chemical kinetic models—a series of persistent and emerging scientific challenges were identified, highlighting the need for deeper integration between three areas: theory, experiments, and modeling. In conclusion, the present article concisely describes present challenges that were identified in each of the technical domains in an effort to streamline and coordinate solutions to accelerate progress in combustion science.

Chemical kinetics↗
DOE OSTI2023

A projection-based analytical Jacobian framework for chemical kinetics applications

A major challenge in simulating complex combustion systems with detailed chemical kinetic models is the cost of integrating the chemical source terms, often done using stiff ODE solvers that require frequent Jacobian evaluations. Using analytically derived Jacobian matrices instead of divided-difference-based numerical Jacobian approximations can significantly reduce the associated computational cost. However, ambiguities arise in the formulation of analytical Jacobians because the chemical state of the system, or state vector, can be expressed in multiple ways, involving variables that are typically not independent from one another. Here, in this work, the consequences of those ambiguities on practical calculations are characterized in detail, and a generalized, projection-based framework is proposed as a mitigation strategy. Performances are assessed in a series of test cases involving a variety of configurations and numerical solution approaches. Results show that with proper treatment, commonly used analytical Jacobian formulations can be considered as equivalent for practical purposes, thereby alleviating concerns that the state vector chosen to express the governing equations and corresponding analytical Jacobian may significantly impact the accuracy of the simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Data-driven chemical kinetic reaction mechanism for F-24 jet fuel ignition

A data-driven chemical kinetic mechanism for the military version of Jet A, F-24, is developed for numerical simulations of the ignition process. The main purpose of this study is to obtain a practical F-24 mechanism across wide temperature and equivalence ratio ranges, with a particular focus on the negative temperature coefficient and low temperature regions. The new mechanism (ARLMech-HC-F24) is based on the HyChem model of a similar fuel and optimized using a micro-genetic algorithm against an experimental ignition delay data set of the target fuel. The development and optimization processes include reaction selection, population creation, shuffled tournament implementation based on a merit function, and child-individual creation for the next generation. Several techniques and parameters are proposed to generate an accurate mechanism through an efficient process. The newly introduced data-driven mechanism based on these techniques shows better merit value convergence and represents the ignition behavior more accurately than that without the techniques. This practical mechanism is suitable for the numerical simulations of the F-24 or Jet A ignition problem, and the suggested strategies can be employed in similar problems of rate coefficients estimation.

42 ENGINEERING↗
DOE OSTI2024

Ignition Delay Times and Chemical Kinetic Model Validation for Hydrogen and Ammonia Blending With Natural Gas at Gas Turbine Relevant Conditions

Ignition delay times from undiluted mixtures of natural gas (NG)/H 2 /Air and NG/NH 3 /Air were measured using a high-pressure shock tube at the University of Central Florida. The combustion temperatures were experimentally tested between 1000 and 1500 K near a constant pressure of 25 bar. As mentioned, mixtures were kept undiluted to replicate the same chemistry pathways seen in gas turbine combustion chambers. Recorded combustion pressures exceeded 200 bar due to the large energy release, hence why these were performed at the high-pressure shock tube facility. The data are compared to the predictions of the NUIGMech 1.1 mechanism for chemical kinetic model validation and refinement. An exceptional agreement was shown for stoichiometric conditions in all cases but strayed at lean and rich equivalence ratios, especially in the lower temperature regime of H 2 addition and all temperature ranges of the baseline NG mixture. Hydrogen addition also decreased ignition delay times by nearly 90%, while NH 3 fuel addition made no noticeable difference in ignition time. NG/NH 3 exhibited similar chemistry to pure NG under the same conditions, which is shown in a sensitivity analysis. Here, the reaction CH 3 + O 2 = CH 3 O + O is identified and suggested as a possible modification target to improve model performance. Increasing the robustness of chemical kinetic models via experimental validation will directly aid in designing next-generation combustion chambers for use in gas turbines, which in turn will greatly lower global emissions and reduce greenhouse effects.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Autoignition of Premixed Liquefied Petroleum Gas in a Rapid Compression Machine: Experimental Results and Chemical Kinetic Mechanism Reduction

Liquefied petroleum gas (LPG) has many properties that make it an attractive alternative fuel such as lower cost than conventional fuels and an established distribution infrastructure. The development of high efficiency, spark ignited LPG engines is currently limited by engine knock and misfire. The knock and misfire limits are further complicated by the wide range of chemical reactivity in LPG, particularly in international markets. In this study, a rapid compression machine (RCM) was used to characterize the effects of variation in LPG fuel reactivity, equivalence ratio, and exhaust gas recirculation (EGR) on autoignition of LPG/oxidizer/inert/EGR blends. Experiments were conducted with 100% propane (C3H8) and blends of propane with propene, ethane, isobutane, and n-butane. EGR was simulated with mixtures of Ar, CO2, CO, and NO at substitution percentages from 0 to 30 mass percent. Equivalence ratio was varied from 0.75 to 1.5. Ignition delay period under homogeneous autoignition conditions was measured at compressed pressures and temperatures of 23 to 25 bar and 701 to 921 K, respectively. Zero-dimensional simulations of the RCM experiments were performed using Chemkin with several detailed chemical kinetic mechanisms to determine their suitability at predicting ignition delay periods. Multiple reduced chemical kinetic mechanisms were created from the NUIGMech1.1 mechanism to determine the optimal balance between accuracy and computational efficiency for future three-dimensional, time-dependent spark-ignited engine computations.

42 ENGINEERING↗
DOE OSTI2021

Automated theoretical chemical kinetics: Predicting the kinetics for the initial stages of pyrolysis

Large scale implementation of high level computational theoretical chemical kinetics offers the prospect for dramatically improving the fidelity of combustion chemical modeling. To facilitate such efforts, we have developed a suite of codes, collectively referred to as AutoMech, that allow for the automatic prediction of the kinetics for large sets of reactions via ab initio transition-state-theory based master-equation calculations. The primary input is simply the mechanism, a dictionary relating chemically identifiable species descriptors (e.g., SMILES or InChIs) to species labels in the mechanism, and a specification of the electronic structure and transition state theory models to be implemented. Here we illustrate the current utility of AutoMech through a study of the initial stages of pyrolysis for 3 sets of fuels: sequences of alkanes, alcohols, and aldehydes. For simplicity, the analysis focuses on abstractions from the fuel by H, CH 3 , and OH, and the decomposition of the resulting radicals. Altogether, there are a total of 166 input channels in these sets (more than 363 forward reactions when expanded to the full set of elementary reactions). The code successfully produces high quality rate estimates (with apparent uncertainties less than a factor of two in limited comparisons with experiment) for > 95% of these. For the radical decomposition reactions, the analysis includes predictions for the pressure dependence of the kinetics. This wide-ranging exploration illustrates (i) the effect of different levels of prediction on the expected accuracy, (ii) the branching between abstractions at different sites for different abstractors, (iii) the dependence of the rates on the chemical structure, and (iv) the variation in radical stabilities across chemical families. These results, as well as the demonstrated feasibility of the methodology, should find further utility in the development of accurate rate expressions for arbitrary fuels. (c) 2020 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Elliott, Sarah N.↗
DOE OSTI2023

Hydrogen and Ammonia Blending With Natural Gas: Ignition Delay Times and Chemical Kinetic Model Validation at Gas Turbine Relevant Conditions

Abstract Ignition delay times from undiluted mixtures of natural gas (NG)/H2/Air and NG/NH3/Air were measured using a high-pressure shock tube at the University of Central Florida. The combustion temperatures were experimentally tested between 1000–1500 K near a constant pressure of 25 bar. As mentioned, mixtures were kept undiluted to replicate the same chemistry pathways seen in gas turbine combustion chambers. Recorded combustion pressures exceeded 200 bar due to the large energy release, hence why these were performed at the high-pressure shock tube facility. The data is compared to the predictions of the NUIGMech 1.1 mechanism for chemical kinetic model validation and refinement. An exceptional agreement was shown for stoichiometric conditions in all cases but strayed at lean and rich equivalence ratios, especially in the lower temperature regime of H2 addition and all temperature ranges of the baseline NG mixture. Hydrogen addition also decreased ignition delay times by nearly 90%, while NH3 fuel addition made no noticeable difference in ignition time. NG/NH3 exhibited similar chemistry to pure NG under the same conditions, which is shown in a sensitivity analysis. The reaction CH3 + O2 = CH3O + O is identified and suggested as a possible modification target to improve model performance. Increasing the robustness of chemical kinetic models via experimental validation will directly aid in designing next-generation combustion chambers for use in gas turbines, which in turn will greatly lower global emissions and reduce greenhouse effects.

Pierro, Michael↗
DOE OSTI2020

CheKiPEUQ Intro 2: Harnessing Uncertainties from Data Sets, Bayesian Design of Experiments in Chemical Kinetics**

When choosing experimental conditions, Bayesian statistical tools can predict the experimental choices which will yield the highest information gain. Experimental choices could be temperature, pressure, reaction time, number of measurements, reactor volume, etc.. Three example analyses are presented here, each using the software Chemical Kinetics Parameter Estimation and Uncertainty Quantification (CheKiPEUQ). Information gain is a measure of reduction of uncertainty in a model's parameters. The three chemical system examples presented each illustrate Bayesian Design of Experiments using information gain. In the first chemical example, temperature selection impacts the information gain for the free energy of reaction in a two-component equilibrium reaction. In the second example, temperature and pressure are explored for a competitive adsorption Langmuir replacement reaction system. Finally, the third example is a catalytic membrane reactor which is a culmination of the previous examples. The catalytic membrane reactor has a complex and nonlinear response in the observables which is solved by numerical evaluation. In the three examples, the experimental conditions are treated as design variables for maximizing information gain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An improved detailed chemical kinetic model for C3-C4 linear and iso-alcohols and their blends with gasoline at engine-relevant conditions

Propanol and butanol isomers have received significant research attention as promising fuel additives or neat biofuels. Robust chemical kinetic models are needed that can provide accurate and efficient predictions of combustion performance across a wide range of engine relevant conditions. Herein, this study seeks to improve the understanding of ignition and combustion behavior of pure C3-C4 linear and iso-alcohols, and their blends with gasoline at engine-relevant conditions. In this work, a kinetic model with improved thermochemistry and reaction kinetics was developed based on recent theoretical calculations of H-atom abstraction and peroxy radical reaction rates. Kinetic model validations are reported, and the current model reproduces the ignition delay times of the C3 and C4 alcohols well. Variations in reactivity over a wide range of temperatures and other operating conditions are also well predicted by the current model. Recent ignition delay time measurements from a rapid compression machine of neat iso-propanol and iso-butanol [Cheng et al., Proc. Combust Inst. (2020)] and blends with a research grade gasoline [Goldsborough et al., Proc. Combust Inst. (2020)] at elevated pressure (20–40 bar) and intermediate temperatures (780–950 K) were used to demonstrate the accuracy of the current kinetic model at conditions relevant to boosted spark-ignition engines. The effects of alcohol blending with gasoline on the autoignition behavior are discussed. The current model captures the suppression of reactivity in the low-temperature and negative-temperature-coefficient (NTC) region when either isopropanol and isobutanol are added to a research grade gasoline. Sensitivity and reaction flux analysis were performed to provide insights into the relevant fuel chemistry of the C3-C4 alcohols.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Chemical Kinetics for the Oxidation of Californium(III) Ions with Select Radiation-Induced Inorganic Radicals (Cl 2 •– and SO 4 •– )

Despite the availability of transuranic elements increasing in recent years, our understanding of their most basic and inherent radiation chemistry is limited and yet essential for accurate interpretation of their physical and chemical properties. Here, in this work, we explore the transient interactions between trivalent californium ions (Cf 3+ ) and select inorganic radicals arising from the radiolytic decomposition of common anions and functional group constituents, specifically the dichlorine (Cl 2 •- ) and sulfate (SO 4 •- ) radical anions. Chemical kinetics, as measured by integrated electron pulse radiolysis and transient absorption spectroscopy techniques, are presented for the reactions of these two oxidizing radicals with Cf 3+ ions. The derived and ionic strength corrected second-order rate coefficients (k) for these radiation-induced processes are k(Cf 3+ + Cl 2 •- ) = (8.28 ± 0.61) × 10 5 M -1 s -1 and k(Cf 3+ + SO 4 •- ) = (9.50 ± 0.43) × 10 8 M -1 s -1 under ambient temperature conditions (22 ± 1 °C).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Probing the Chemical Kinetics of Minimalist Functional Group Gasoline Surrogates

We report surrogate mixtures are routinely used for understanding gasoline fuel combustion in engine simulations. The general trend in surrogate formulation has been to increase the number of fuel components in a mixture to better emulate real fuel properties. Recently, a new surrogate design strategy based on functional group analysis of real gasolines was proposed using a minimal number of species [minimalist functional group (MFG)-approach]. MFG surrogates (having just one or two components) could experimentally capture the ignition delay time (IDT), threshold sooting index, and smoke point of different gasoline fuels with hundreds of components. However, other combustion characteristics were not explored, and kinetic modeling of MFG surrogates was not reported. These aspects are addressed in this paper, where the combustion behavior of MFG surrogates for various gasolines was assessed by simulating IDT, jet-stirred reactor oxidation, and premixed laminar flame speeds using chemical kinetic modeling. MFG simulations were compared with experimental data of the real gasolines as well as with the more complex multicomponent (five to nine species) surrogates. This study reveals that binary MFG surrogate mixtures are capable of accurately simulating the combustion behavior of more complex gasoline fuels with hundreds of components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗