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Frhodo: A program for simulating chemical kinetic measurements and optimizing kinetic mechanisms
Chemical kinetic simulations are frequently used to extract kinetic and mechanistic information from experimental data by fitting simulations to the data. For simple systems of consecutive single channel reactions this is a relatively straightforward task. However, as the complexity of the system increases and particularly for systems involving competitive multi-channel reactions manually optimizing a mechanism to obtain the best fits to a range of experimental data quickly becomes a time-intensive and challenging process, especially when rate coefficients have pressure and temperature dependencies. There is considerable potential for exploiting automated optimization methods to rapidly screen reaction mechanisms and optimize the fit by adjusting rate coefficients within well-defined constraints. A new chemical kinetics simulation program, Frhodo, has been developed for this purpose. The program allows either manual simulation of individual experiments or fully automated optimization against a range of experimental data by adjusting user selected reactions within user defined constraints. Frhodo incorporates machine learning-based optimization routines that work by either minimizing standardized residuals or through Bayesian parameter estimation. Frhodo's optimization capabilities are demonstrated by reexamining two previously studied systems of relevance to combustion. Dissociation of diacetyl followed by recombination of methyl radicals is an example of a sequence of single channel, consecutive reactions. Pyrolysis of 2-methyl furan exemplifies multi-channel, unimolecular reactions that are often encountered and have temperature and pressure dependencies in the rate coefficients of the channels and branching ratios between them. For both systems the optimization routines resulted in solutions similar to the original studies. Finally, comments are made on the strengths and limitations of the approach.
An experimental and chemical kinetic modeling study of 4-butoxyheptane combustion
Here, the combustion kinetics of a novel oxygenated bioblendstock for diesel, 4-butoxyheptane (4-BH), was investigated experimentally using a flow reactor and a heated, high-pressure shock tube. The flow reactor experiments employed oxygen as the oxidizer and helium as the diluent with oxidation conducted at atmospheric pressure and 10 bar for temperatures from 400 to 1000 K at 20-K intervals. The fuel, oxidizer, and diluent flow rates were varied at different temperatures to maintain a constant initial fuel mole fraction of 1000 ppm, with stoichiometric equivalence ratio, and a residence time of 2.0 s. The reacted gas was fed to two separate GC systems that could qualitatively and quantitatively detect product species. Additionally, real fuel-air ignition delay time (IDT) data were collected using a heated, high-pressure shock-tube facility. Fuel lean (φ = 0.5) and stoichiometric (φ = 1.0) mixtures were investigated at 10 atm as well as at 30 atm for the fuel lean case for temperatures between 847 and 1259 K. A detailed chemical kinetics mechanism was developed to model the product distribution from the flow reactor and IDTs from the shock tube. The proposed model was able to predict the double NTC behavior in flow reactor experiments reasonably well. Model predictions at low temperatures were observed to be highly sensitive to the rate constants of ketohydroperoxide (KHP) decomposition in the case of the OOH group in α position which were modeled based on existing literature studies on ethers. It was noted that in the absence of theoretical or experimental studies, the rate constants for KHP decomposition used in the literature were empirically set. Additional studies are required to address the gap in model prediction obtained in this study and to reduce the uncertainty in kinetics models for ether oxidation. Predicted product concentrations and IDTs showed some quantitative agreement with experimental data, but the overall reactivity of the IDTs is underpredicted. Additionally, significant deviation is observed for the IDT results at 10 atm for the stoichiometric case with minor deviations for the other cases. The reaction pathways to the missing products were then further analyzed theoretically through quantum-mechanical calculations.
Modeling of the HiPco process for carbon nanotube production. I. Chemical kinetics
A chemical kinetic model is developed to help understand and optimize the production of single-walled carbon nanotubes via the high-pressure carbon monoxide (HiPco) process, which employs iron pentacarbonyl as the catalyst precursor and carbon monoxide as the carbon feedstock. The model separates the HiPco process into three steps, precursor decomposition, catalyst growth and evaporation, and carbon nanotube production resulting from the catalyst-enhanced disproportionation of carbon monoxide, known as the Boudouard reaction: 2 CO(g)-->C(s) + CO2(g). The resulting detailed model contains 971 species and 1948 chemical reactions. A second model with a reduced reaction set containing 14 species and 22 chemical reactions is developed on the basis of the detailed model and reproduces the chemistry of the major species. Results showing the parametric dependence of temperature, total pressure, and initial precursor partial pressures are presented, with comparison between the two models. The reduced model is more amenable to coupled reacting flow-field simulations, presented in the following article.
An out-of-distribution-aware autoencoder model for reduced chemical kinetics
While detailed chemical kinetic models have been successful in representing rates of chemical reactions in continuum scale computational fluid dynamics (CFD) simulations, applying the models in simulations for engineering device conditions is computationally prohibitive. To reduce the cost, data-driven methods, e.g., autoencoders, have been used to construct reduced chemical kinetic models for CFD simulations. Despite their success, data-driven methods rely heavily on training data sets and can be unreliable when used in out-of-distribution (OOD) regions (i.e., when extrapolating outside of the training set). In this paper, we present an enhanced autoencoder model for combustion chemical kinetics with uncertainty quantification to enable the detection of model usage in OOD regions, and thereby creating an OOD-aware autoencoder model that contributes to more robust CFD simulations of reacting flows.Here, we first demonstrate the effectiveness of the method in OOD detection in two well-known datasets, MNIST and Fashion-MNIST, in comparison with the deep ensemble method, and then present the OOD-aware autoencoder for reduced chemistry model in syngas combustion.
A hybrid computer program for rapidly solving flowing or static chemical kinetic problems involving many chemical species
A hybrid chemical kinetic computer program was assembled which provides a rapid solution to problems involving flowing or static, chemically reacting, gas mixtures. The computer program uses existing subroutines for problem setup, initialization, and preliminary calculations and incorporates a stiff ordinary differential equation solution technique. A number of check cases were recomputed with the hybrid program and the results were almost identical to those previously obtained. The computational time saving was demonstrated with a propane-oxygen-argon shock tube combustion problem involving 31 chemical species and 64 reactions. Information is presented to enable potential users to prepare an input data deck for the calculation of a problem.
Chemical Kinetics of the Autoxidation of Poly(ethylenimine) in CO 2 Sorbents
The oxidative degradation rates of a CO 2 sorbent composed of a mesoporous alumina impregnated with poly- (ethylenimine) (PEI) are measured under systematically varied conditions and a reaction rate law is created. Good agreement is shown between the rate of oxidation obtained via in situ calorimetric heat measurement during oxidative degradation reactions and the loss of CO 2 capture performance presented as amine efficiency (mol CO 2 /mol amine). PEI mass loss and elemental composition are tracked over the course of the reaction and used in conjunction with the oxidation rate measurements to shed insight into the oxidation reaction(s). These data, in combination with measurements of the heat of reaction, suggest a common reaction set across the range of temperatures, oxygen concentrations, and sorbent compositions tested. The data are consistent with the basic autoxidation scheme (BAS), the accepted mechanism of autoxidation of aliphatic polymers. We propose a lumped kinetic model to describe the oxidation reaction set and estimate an activation energy of 105 kJ/mol and an oxygen reaction order of 0.5–0.7 from the data accordingly. Furthermore, these parameters can be incorporated into process cycle models to estimate the material lifetime, a critical uncertainty in the deployment of DAC technologies.
General chemical kinetics computer program for static and flow reactions, with application to combustion and shock-tube kinetics
A general chemical kinetics program is described for complex, homogeneous ideal-gas reactions in any chemical system. Its main features are flexibility and convenience in treating many different reaction conditions. The program solves numerically the differential equations describing complex reaction in either a static system or one-dimensional inviscid flow. Applications include ignition and combustion, shock wave reactions, and general reactions in a flowing or static system. An implicit numerical solution method is used which works efficiently for the extreme conditions of a very slow or a very fast reaction. The theory is described, and the computer program and users' manual are included.
Zero Order Reactioin Kinetics: Enabling the use of Detailed Chemical Kinetics in Combustion Simulations (Final CRADA Report)
This was a collaborative effort between Lawrence Livermore National Security, LLC (LLNS), as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Gamma Technologies, LLC (GT or Participante), to incorporate the ability to access LLNL chemical kinetics technologies while using GT-SUITE, GT’s market leading engine simulation software. At the end of the project, LLNL has released Zero-RK version 3.5 with zero- and one-dimensional (0-D and 1-D) solver functionality that interfaces with GT’s GT-SUITE v2023 and later releases. GT has tested its product to assure their customers that the interface can provide reduction in chemistry solution time for detailed chemistry simulations. The process has also positioned GT to easily benefit from future improvements of the Zero-RK suite of tools developed under the DOE Vehicle Technologies Office.
Chemical kinetics and modeling of planetary atmospheres
A unified overview is presented for chemical kinetics and chemical modeling in planetary atmospheres. The recent major advances in the understanding of the chemistry of the terrestrial atmosphere make the study of planets more interesting and relevant. A deeper understanding suggests that the important chemical cycles have a universal character that connects the different planets and ultimately link together the origin and evolution of the solar system. The completeness (or incompleteness) of the data base for chemical kinetics in planetary atmospheres will always be judged by comparison with that for the terrestrial atmosphere. In the latter case, the chemistry of H, O, N, and Cl species is well understood. S chemistry is poorly understood. In the atmospheres of Jovian planets and Titan, the C-H chemistry of simple species (containing 2 or less C atoms) is fairly well understood. The chemistry of higher hydrocarbons and the C-N, P-N chemistry is much less understood. In the atmosphere of Venus, the dominant chemistry is that of chlorine and sulfur, and very little is known about C1-S coupled chemistry. A new frontier for chemical kinetics both in the Earth and planetary atmospheres is the study of heterogeneous reactions. The formation of the ozone hole on Earth, the ubiquitous photochemical haze on Venus and in the Jovian planets and Titan all testify to the importance of heterogeneous reactions. It remains a challenge to connect the gas phase chemistry to the production of aerosols.
Theory of internal relaxation in chemical kinetics
Internal relaxation theory in chemical kinetics
COMPLEX CHEMICAL KINETICS IN SUPERSONIC NOZZLE FLOW
Chemical kinetics in supersonic nozzle flow
Transitory sensitivity in automatic chemical kinetic mechanism analysis
Abstract Detailed chemical kinetic mechanisms are necessary for resolving many important chemical processes. As the chemistry of smaller molecules has become better grounded and quantum chemistry calculations have become cheaper, kineticists have become interested in constructing progressively larger kinetic mechanisms to model increasingly complex chemical processes. These large kinetic mechanisms prove incredibly difficult to refine and time‐consuming to interpret. Traditional sensitivity analysis on a large mechanism can range from inconvenient to practically impossible without special techniques to reduce the computational cost. We first present a new time‐local sensitivity analysis we term transitory sensitivity analysis. Transitory sensitivity analysis is demonstrated in an example to accurately identify traditionally sensitive reactions at an 18,000x speed up over traditional sensitivities. By fusing transitory sensitivity analysis with more traditional time‐local branching, pathway, and cluster analyses, we develop an algorithm for efficient automatic mechanism analysis. This automatic mechanism analysis at a time point is able to identify the reactions a target is most sensitive to using transitory sensitivity analysis and then propose hypotheses why the reaction might be sensitive using branching, pathway, and cluster analyses. We implement these algorithms within the reaction mechanism simulator (RMS) package, which enables us to report the automatic mechanism analysis results in highly readable text formats and in molecular flux diagrams.
Numerical Methods of Solution of Chemical Kinetics Equations
Numerical analysis of chemical kinetics in reacting gas equations applied to rocket nozzle and plume flows
A detailed chemical kinetic modeling and experimental investigation of the low- and high-temperature chemistry of n-butylcyclohexane
Chemical kinetic models of gasoline, jet, and diesel fuels and their mixtures with bioderived fuels are needed to assess fuel property effects on efficiency, emissions, and other performance metrics in internal combustion and gas turbine engines. As these real fuels have too many fuel components to be included in a chemical kinetic model, surrogate fuels containing fewer components are used to represent them. These surrogate fuels mimic the chemical classes or molecular structures contained in the real fuel. One of the important chemical classes in gasoline, jet, and diesel fuels comprises cyclohexanes. Cyclohexanes comprise about 30% or more by weight in diesel fuel. Also, Mueller et al proposed n-butylcyclohexane (nBCH) as a component in a nine-component surrogate palette to represent the ignition properties, distillation curve, density, and molecular structures of a diesel certification fuel. Herein, experimental measurements of the ignition delay times (IDTs) of nBCH in a shock tube and in a rapid compression machine are reported over a wide range of temperature, pressure, and equivalence ratio important for enabling the validation of a chemical kinetic model for nBCH for combustion in diesel engines. The range of conditions are temperatures of 630–1420 K, pressures of 10, 30, and 50 bar, and equivalence ratios of 0.3, 0.5, 1.0, and 2.0 in ‘air’. A detailed chemical model is developed for nBCH to simulate its ignition at both low and high-temperature conditions and at relevant elevated pressures. The experimentally measured IDTs are used to improve and validate the chemical kinetic model.
New insights into fuel blending effects: Intermolecular chemical kinetic interactions affecting autoignition times and intermediate-temperature heat release
Fuel blending effects on chemically-dominated fuel properties, such as gasoline anti-knock quality, are influenced by fundamental chemical kinetic interactions between the blending agent and the base fuel. Historically, quantification of such interactions has focused on changes to the radical pool, including $\dot{O}$H and HO 2 , while intermolecular interactions pertaining to carbonated, non-fuel-specific intermediates are typically overlooked. In this regard, this work aims to derive new insight into intermolecular chemical kinetic interactions that are intrinsic to fuel blending effects via a case study on blends of 0–30% ethanol (by volume) into FGF-LLNL (a multi-component gasoline surrogate for FACE-F research gasoline) using a rapid compression machine at a diluted/stoichiometric fuel loading, compressed pressure of 40 bar and low- to intermediate-temperature regimes that are representative of boosted SI engine operation. Ethanol blending effects on the intermediate temperature heat release (ITHR) of FGF-LLNL are characterized using experimental measurements, where ethanol is found to promote the extent of ITHR and suppress the transition from ITHR to main ignition. Chemical kinetic modeling is undertaken using a recently updated gasoline surrogate model. Sensitivity analyses on ITHR characteristics further corroborate the ethanol blending effects, and highlight the significant dependence of ITHR on both fuel-specific and non-fuel-specific reactions. An approach allowing comprehensive characterization of the complex intermolecular chemical kinetic interactions between constitutes in a fuel blend is then proposed. Application of the approach to FGF-LLNL/E0–E30 reveals that ethanol perturbs the heat release and autoignition characteristics of FGF-LLNL not only by directly changing the $\dot{O}$H and HO 2 radical pools via fuel-specific reactions, but also through intermolecular interactions where participating intermediates can be produced and consumed by various sub-chemistries. Disabling the intermolecular interactions in carbonated species between ethanol and FGF-LLNL sub-chemistries leads to somewhat slower ITHR evolution and lower ignition reactivity. The role of the individual intermolecular interaction is also characterized using the proposed approach. Lastly, implications of intermolecular interactions for future studies that aim to improve model performance are highlighted, where it is found that further investigations on the core C0-C4 chemistry are needed for developing highly accurate chemistry models for complex fuel blends.
Key Chemical Kinetic Steps in Reaction Mechanisms for Fuels from Biomass: A Perspective
Detailed chemical kinetic modeling has been a significant part of combustion research since the entry of the computer into the research community. For most of that time, fuels have largely been provided from petrochemicals, and the combustion chemistry that was developed reflected that source of fuels. Furthermore, renewable fuels from biomass have always made important contributions as fuel sources. Current trends show that renewable fuels are gaining an even more important role as fuel sources, and chemical kinetic modeling of those fuels is playing an essential role in these advances. Interactions between fuels research and chemical kinetic modeling are discussed in this paper, with emphasis on the close and continuous coupling between them. In many cases, new fuels from biomass have structural or compositional features never before seen in real fuels, so entirely new reaction mechanisms are required.