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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Probing the Effects of NO x and SO x Impurities on Oxy-Fuel Combustion in Supercritical CO 2 : Shock Tube Experiments and Chemical Kinetic Modeling

The direct-fired supercritical carbon dioxide cycles are one of the most promising power generation methods in terms of their efficiency and environmental friendliness. Two important challenges in implementing these cycles are the high pressure (300 bar) and high CO 2 dilution (>80%) in the combustor. The design and development of supercritical oxy-combustors for natural gas require accurate reaction kinetic models to predict the combustion outcomes. The presence of a small amount of impurities in natural gas and other feed streams to oxy-combustors makes these predictions even more complex. During oxy-combustion, trace amounts of nitrogen present in the oxidizer is converted to NO x and gets into the combustion chamber along with the recirculated CO 2 . Similarly, natural gas can contain a trace amount of ammonia and sulfurous impurities that get converted to NO x and SO x and get back into the combustion chamber with recirculated CO 2 . In this work, a reaction model is developed for predicting the effect of impurities such as NO x and SO x on supercritical methane combustion. The base mechanism used in this work is GRI Mech 3.0. H 2 S combustion chemistry is obtained from Bongartz et al. while NOx chemistry is from Konnov. The reaction model is then optimized for a pressure range of 30–300 bar using high-pressure shock tube data from the literature. It is then validated with data obtained from the literature for methane combustion, H 2 S oxidation, and NO x effects on ignition delay. The effect of impurities on CH 4 combustion up to 16 atm is validated using NO x -doped methane studies obtained from the literature. In order to validate the model for high-pressure conditions, experiments are conducted at the UCF shock tube facility using natural gas identical mixtures with N 2 O as an impurity at ~100 bar. Current results show that there is a significant change in ignition delay with the presence of impurities. A comparison is made with experimental data using the developed model and predictions are found to be in good agreement. The model developed was used to study the effect of impurities on CO formation from sCO 2 combustors. It was found that NO x helps in reducing CO formation while the presence of H 2 S results in the formation of more CO. The reaction mechanism developed herein can also be used as a base mechanism to develop reduced mechanisms for use in CFD simulations.

Energy & Fuels↗
DOE OSTI2024

Partially cracked ammonia mixture combustion in gas turbine combustors

Ammonia is gaining popularity for single fuel use in existing gas turbines, as it is carbonless, has higher hydrogen content per unit volume than liquid hydrogen, and facilitates easy storage and handling. However, the low flame speed of ammonia makes it prone to flame blow off and remains the chief concern for its use in power generation. Following previous studies that have shown improved combustion performance by partially cracking the fuel, in this computational study, efficacy of partially cracked ammonia as a replacement fuel for natural gas is evaluated. A high-pressure optically accessible combustor operated at ~10 bar pressure with non-vitiated heated air was used as the test platform. This combustor was equipped with a novel multifuel multi-tube micromixing injector (M3 injector). High resolution simulations of the flow fields both in the injector as well as the combustor were performed to understand the fuel mixing in the injector and in the inlet region of the combustor. These modeling results showed that the injector was highly effective for achieving mixture homogeneity at the entrance of the combustor for ammonia and natural gas injection, whereas, for hydrogen an earlier injection facilitating longer residence time would be beneficial. Also, these simulations show that while harnessing waste heat the ideal fuel dissociation fraction is between 0.4 and 0.55 for optimal operation.

Ammonia↗
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 OSTI2020

Numerical Investigation of Fuel Property Effects on Mixed-Mode Combustion in a Spark-Ignition Engine

In this research, lean mixed-mode combustion is numerically investigated using computational fluid dynamics (CFD) in a spark-ignition engine. A new E30 fuel surrogate is developed using a neural network model with matched octane numbers. A skeletal mechanism is also developed by automated mechanism reduction and by incorporating a NO x submechanism. A hybrid approach that couples the G-equation model and the well-stirred reactor model is employed for turbulent combustion modeling. The developed CFD model is shown to well predict pressure and apparent heat release rate (AHRR) traces compared with experiment. Two types of combustion cycles (deflagration-only and mixed-mode cycles) are observed. The mixed-mode cycles feature early flame propagation and subsequent end-gas auto-ignition, leading to two distinctive AHRR peaks. The validated CFD model is then employed to investigate the effects of NO x chemistry. The NO x chemistry is found to promote auto-ignition through the residual gas, while the deflagration phase remains largely unaffected. Sensitivity analysis is finally performed to understand effects of fuel properties, including heat of vaporization (HoV) and laminar flame speed (S L ). An increased HoV tends to suppress auto-ignition through charge cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased S L is found to significantly promote both flame propagation and end-gas auto-ignition. The promoting effect of S L on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end-gas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Probing O 2 -dependence of tetrahydrofuranyl reactions via isomer-resolved speciation

Low-temperature oxidation of tetrahydrofuran involves competing reactions that depend on temperature, pressure, and oxygen concentration, including ring-opening and subsequent oxidation of initial radicals ($\dot{R}$), HOO-elimination yielding dihydrofuran isomers, and the formation of peroxy radicals ($RO\dot{O}$). Here, the latter species, upon isomerization, lead to hydroperoxy-substituted radicals ($\dot{Q}OOH$) that undergo reaction either via unimolecular decomposition or second-O 2 -addition. Quantitative measurements of partially oxidized intermediates formed from each type of reaction provide critical constraints that are required for accurate modeling of combustion. To examine the influence of temperature and oxygen concentration on intermediates from tetrahydrofuran, isomer-resolved speciation measurements were conducted at 810 Torr in a jet-stirred reactor (JSR) from 500 – 1000 K. Resulting from negative-temperature coefficient behavior, species concentrations peaked at two temperatures, 600 K and 800 K, which were then selected for separate experiments to quantify O 2 -dependence using concentrations of 0.37 • 10 18 – 7.40 • 10 18 molecules cm –3 .

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

Tracking the reaction networks of acetaldehyde oxide and glyoxal oxide Criegee intermediates in the ozone-assisted oxidation reaction of crotonaldehyde

The reaction of unsaturated compounds with ozone (O 3 ) is recognized to lead to the formation of Criegee intermediates (CIs), which play a key role in controlling the atmospheric budget of hydroxyl radicals and secondary organic aerosols. The reaction network of two CIs with different functionality, i.e. acetaldehyde oxide (CH 3 CHOO) and glyoxal oxide (CHOCHOO) formed in the ozone-assisted oxidation reaction of crotanaldehyde (CA), is investigated over a temperature range between 390 K and 840 K in an atmospheric pressure jet-stirred reactor (JSR) at a residence time of 1.3 s, stoichiometry of 0.5 with a mixture of 1% crotonaldehyde, 10% O 2 , at an fixed ozone concentration of 1000 ppm and 89% Ar dilution. Molecular-beam mass spectrometry in conjunction with single photon tunable synchrotron vacuum-ultraviolet (VUV) radiation is used to identify elusive intermediates by means of experimental photoionization energy scans and ab initio threshold energy calculations for isomer identification. Addition of ozone (1000 ppm) is observed to trigger the oxidation of CA already at 390 K, which is below the temperature where the oxidation reaction of CA was observed in the absence of ozone. The observed CA + O 3 product, C 4 H 6 O 4 , is found to be linked to a ketohydroperoxide (2-hydroperoxy-3-oxobutanal) resulting from the isomerization of the primary ozonide. Products corresponding to the CIs uni- and bi-molecular reactions were observed and identified. A network of CI reactions is identified in the temperature region below 600 K, characterized by CIs bimolecular reactions with species like aldehydes, i.e., formaldehyde, acetaldehyde, and crotonaldehyde and alkenes, i.e., ethene and propene. The region below 600 K is also characterized by the formation of important amounts of typical low-temperature oxidation products, such as hydrogen peroxide (H 2 O 2 ), methyl hydroperoxide (CH 3 OOH), and ethyl hydroperoxide (C 2 H 5 OOH). Detection of additional oxygenated species such as alcohols, ketene, and aldehydes are indicative of multiple active oxidation routes. This study provides important information about the initial step involved in the CIs assisted oligomerization reactions in complex reactive environments where CIs with different functionalities are reacting simultaneously. It provides new mechanistic insights into ozone-assisted oxidation reactions of unsaturated aldehydes, which is critical for the development of improved atmospheric and combustion kinetics models.

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

Do not forget the electrons: Extending moderately-sized nuclear networks for multidimensional hydrodynamic codes

Context.Nuclear networks are widely used coupled with hydrodynamical simulations of explosive scenarios to account for the change of nuclear species and energy generation rate due to nuclear reactions. In this way, there is a feedback mechanism between the hydrodynamical state and the nuclear processes. Unfortunately, the timescale of nuclear reactions is orders of magnitude smaller than the dynamical timescale that drives hydrodynamical simulations. Therefore, these nuclear networks are usually very small, reduced in most cases to a dozen elements, especially when simulations are carried out in more than one dimension. Aims.We present here an extended nuclear network, with 90 species, designed for being coupled with hydrodynamic simulations, which includes neutrons, protons, electrons, positrons, and the corresponding neutrino and anti-neutrino emission. This network is also coupled with temperature, making it extremely robust and, together with its size, unique of its kind. The inclusion of electron captures on free protons makes the network very appropriate for multidimensional studies of Type Ia supernova explosions, especially when the exploding object is a massive white dwarf. Methods.We perform several tests that are relevant to simulate explosive scenarios, such as Type Ia supernovae and core-collapse supernovae. We compare the results of the 90 nuclei network with a standardα-chain network with 14 elements to evaluate the differences in the energy generation rate. We also evaluate the relevance of including the electrons in the network in terms of generated yields and how it affects the pressure of a degenerate fluid such as that of white dwarfs. The results obtained with the 90-nuclei network have been verified with a much larger 2000-nuclei network built from REACLIB (WinNet), in terms of nuclear energy generation rate, pressure, and produced yields. Results.The results obtained with the proposed medium-sized network compare fairly well, to a few percent, with those computed withWinNetin scenarios reproducing the gross physical conditions of current Type Ia supernova explosion models. In those cases where the carbon and oxygen fuel ignites at high density, the high-temperature plateau typical of the nuclear statistical equilibrium regime is well defined and stable, allowing large integration time steps. We show that the inclusion of electron captures on free protons substantially improves the estimation of the electron fraction of the mixture. Therefore, the pressure is better determined than in networks where electron captures are excluded, which will ultimately lead to more reliable hydrodynamic models. Explosive combustion of helium at low density, occurring near the surface layer of a white dwarf, is also better described with the proposed network, which gives nuclear energy generation rates much closer toWinNetthan typical reduced alpha networks. Conclusions.A nuclear network withN= 90 species, including electrons, aimed at multidimensional calculations of supernova explosions is described and verified. The proposed network is suitable for the study of Type Ia supernova explosions because it provides better values of pressure and electron abundance than other existing networks with smaller or even a similar size but without including electron capture processes.

Astronomy & Astrophysics↗
DOE OSTI2020

Nucleation of soot: experimental assessment of the role of polycyclic aromatic hydrocarbon (PAH) dimers

The irreversible dimerization of polycyclic aromatic hydrocarbons (PAHs) – typically pyrene (C 16 H 10 ) dimerization – is widely used in combustion chemistry models to describe the soot particle inception step. This study concerns itself with the detection and identification of dimers of flame-synthesized PAH radicals and closed-shell molecules and an experimental assessment of the role of these PAH dimers for the nucleation of soot. To this end, flame-generated species were extracted from an inverse co-flow flame of ethylene at atmospheric pressure and immediately diluted with excess nitrogen before the mixture was analyzed using flame-sampling tandem mass spectrometry with collision-induced fragmentation. Signal at m/z = 404.157 (C 32 H 20 ) and m/z = 452.157 (C 36 H 20 ) were detected and identified as dimers of closed-shell C 16 H 10 and C 18 H 10 monomers, respectively. A complex between a C 13 H 9 radical and a C 24 H 12 closed-shell PAH was observed at m/z = 465.164 (C 37 H 21 ). However, a rigorous analysis of the flame-sampled mass spectra as a function of the dilution ratio, defined as the ratio of the flow rates of the diluent nitrogen to the sampled gases, indicates that the observed dimers are not flame-born, but are produced in the sampling line. In agreement with theoretical considerations, this paper provides experimental evidence that pyrene dimers cannot be a key intermediate in particle inception at elevated flame temperatures.

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

High-Accuracy Simulations to Model Pyrometallurgical Processes in a Secondary Lead Reverberatory Furnace

The US manufacturing industry produces about 1.3 million tons of refined lead each year using secondary sources consisting mainly of lead batteries. ORNL is partnering with Gopher resource, the second largest lead recycling company in the United States, and GTI, to develop a high-fidelity CFD model of a directly fired, reverberatory-style, secondary lead furnace. These High Performance Computing (HPC) simulations are aimed to use first principles modeling for combustion and melting processes of the secondary lead feed while accounting for complex interphase interactions between the gas, solid charge (lead) material, slag, and metal phases. Through validation against operating plant data, this effort will enable significant improvements in design, operational parameters, and energy efficiency, thus improving productivity and refractory lifetime of secondary lead melting furnaces. Estimated savings/reduction of, at least, 1 trillion BTU, 1 million ton/year of greenhouse gas emissions, and $\$50$ million/year to the US lead industry can be expected. ORNL resources and expertise in high-performance computing and multicomponent, multiphase flows were utilized to realize this goal while advancing the understanding of the smelting and melting processes occurring within the furnace.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Modeling of thermal and kinetic processes in non-equilibrium plasma ignition applied to a lean combustion engine

In recent years novel ignition systems have been developed to enable stable and efficient engine operations with lean mixtures. Among them, radio-frequency corona ignition systems create discharges that involve a much wider region compared to traditional spark, and produce non equilibrium plasma with high levels of active radicals and excited species. These devices considerably increase the early flame growth speed and extend stable operating limits. With the aim of expanding the knowledge on high efficiency lean-burn SI engines, this paper investigates and compares the combustion development generated by spark and corona ignitions through computational fluid dynamics, within the Reynolds-Averaged Navier-Stokes framework for turbulence modeling. In order to simultaneously take thermal and chemical effects into account, the Perfectly Stirred Reactor combustion model is used. Experimental data are also collected for validation in an optical access engine, for different mixture levels, from stoichiometric to very lean. Furthermore, the faster burn rate generated by the corona system in the initial stage of the combustion is well predicted by the simulations, in all the relative air-fuel ratio conditions. Remarkably, as the mixture becomes lean, simulations are able to capture the non-linear transition from fast to slow kernel growth, before a self-sustainable flame propagation is established. This correlates very well with the measured engine cyclic variability and the corresponding steep change in the duration of the flame kernel formation. Ultimately, this study highlights the important role of the atomic oxygen, as active radical, in promoting and enhancing the combustion initiated by a corona discharge, in addition to the volumetric ignition effect. By contrast, the validated simulations allow to explain that the high-temperature thermal plasma generated in a traditional spark discharge is insensitive to kinetic aspects.

42 ENGINEERING↗
DOE OSTI2020

Autoignition of CRC diesel surrogates at low temperature combustion conditions: Rapid compression machine experiments and modeling

As federal programs require increasingly stringent engine emissions and fuel economy standards, these ambitions can only be met if next-generation combustion technology is developed focusing on high-efficiency and low-emissions engines. Recent research has indicated the need to operate engines at higher compression ratios and with low temperature combustion (LTC) to achieve the needed gains in engine efficiency and reductions in emissions. Because there is a lack of understanding of the chemistry of diesel fuel components and their mixtures at these LTC conditions, this limits the ability to develop predictive chemical kinetic models that can be used to optimize engine combustion. The current study aims to fill in gaps in fundamental combustion data on surrogate fuel mixtures relevant to diesel fuels. Specifically, four multicomponent diesel surrogates formulated by the Coordinating Research Council (CRC) to emulate an ultra-low-sulfur research-grade #2 certification diesel fuel (CFA), namely V0a (4 components), V0b (5 components), V1 (8 components), and V2 (9 components), have been investigated in a rapid compression machine (RCM) through determination of total and first-stage ignition delay times. Autoignition characteristics of lean to rich fuel/O 2 /N 2 mixtures, for the four CRC surrogates and CFA, have been measured using an RCM at LTC relevant pressures and temperatures, in the ranges of 10–20 bar and 650–1000 K, respectively. The equivalence ratios have been varied by independently changing the oxygen mole fraction and the fuel mole fraction in the test mixtures, thereby illustrating the individual effects of oxygen concentration and fuel loading on diesel autoignition. Autoignition results of these four CRC surrogates are compared among them and with those of CFA. Some degree of agreement in autoignition response between each CRC surrogate and CFA is observed, while discrepancies are also identified and discussed. In addition, a detailed chemical kinetic model for diesel surrogates has been developed and validated against these newly-acquired RCM data. We find that this model shows reasonable agreement with the overall ignition delay time results of the current RCM experiments. Chemical kinetic analyses of the developed model were further conducted to help identify the reactions controlling the autoignition processes and the consumption of fuel components in CRC surrogates.

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

Influence of Equation-of-States on Supercritical CO2 Combustion Mixtures

Abstract Fossil fuel based direct-fired supercritical CO2 (sCO2) cycles are gaining the attention of industry, academia, and government due to their remarkable efficiency and carbon capture at high-source temperatures. Modeling plays an important role in the development of sCO2 combustors because experiments are very expensive at the designed operating conditions of these direct-fired cycles. Inaccurate density estimates are detrimental to the simulation output. Hence, this work focuses on comprehensive evaluation of the influence and applicability of various equation-of-states (EOS) which are being used in the supercritical combustion modeling literature. A state-of-the-art supercritical combustion modeling methodology is used to simulate counter-flow supercritical CO2 flames by using various equation-of-states. The results show that using the corresponding state principle to evaluate compressibility factor is not accurate. Also, van der Waal type EOSs predictions can be as accurate as complex Benedict–Webb–Rubin EOSs; hence van der Waal EOSs are more suitable to simulate sCO2 combustor simulations. Non-ideal effects are significant under the operating conditions considered in this work. The choice of EOS significantly influences the flame structure and heat release rate. Also, assuming the binary interaction parameter as zero is reasonable in sCO2 combustion simulations.

Energy & Fuels↗
DOE OSTI2021

Transforming Energy through Computational Excellence. Exascale Computing: Combustion; Deep Learning for Presumed Probability Density Function (PDF) Models

NREL researchers use advanced machine learning techniques to define improved methods using deep learning models to resolve reacting flows in turbulent combustion flows, reducing the computational burden, increasing computational speed, and improving accuracy. These advancements reduce cost and improve fidelity of rapid-turn-around engineering calculations.

combustion↗
DOE OSTI2025

Chemical Reactor Network Modeling of Ammonia Rich-Quench-Lean Combustion Using a Partially Stirred Reactor Approach

Ammonia is a promising alternative to hydrogen with high energy density and favorable storage and transport characteristics. However, low flammability and a propensity for high nitrogen oxide (NO x ) emissions make direct utilization challenging. Recently, two-stage rich-quench-lean (RQL) combustion strategies have shown promise in achieving low NO x emissions with ammonia. In this approach, the rich stage serves to oxidize a portion of the fuel while thermally decomposing as much of the remaining ammonia as possible, generating hydrogen. In the second (lean) stage, air is rapidly introduced, burning out the hydrogen and residual ammonia. Two-stage RQL combustion of ammonia has been investigated in the open literature both experimentally and numerically. In general, idealized chemical reactor network (CRN) models predict NO x concentrations below those of 2D/3D computational fluid dynamics models and experiments. The primary drivers of these discrepancies may be largely attributed to finite rate mixing nonadiabatic operation. The typical CRN model is comprised of a perfectly-stirred-reactor (PSR), followed by a plug-flow-reactor (PFR), meant to represent the flame, and postflame zones, respectively. In the two-stage RQL approach two PSR-PFR networks are arranged sequentially, corresponding to the rich and lean stages, with secondary air injection in between. In the authors' past work, this arrangement has demonstrated the significant sensitivity of exit NO x to the rich stage equivalence ratio, while the amount of secondary air injection was shown to be less critical. In this paper, the CRN model is extended to (1) include the impacts of heat loss and (2) utilize a partially-stirred-reactor (PaSR) approach to study the impacts of mixing on emissions performance. Varying amounts of heat loss are applied to the rich relaxation zone to understand emissions performance and changes to optimization of equivalence ratio and residence time. Premixed and nonpremixed configurations are considered in the rich stage PaSR, with varying degrees of mixing intensity to study the interaction between mixing, transport, and kinetic timescales. Critically, the impact of mixing between hot products and secondary air injection is studied to understand practical injector needs. Results show unburnt ammonia leaving the rich stage as a primary contributor to NO x emissions – driven both by increased heat loss and reduced mixing rates. Furthermore, heat losses have been shown to create conditions that are conducive to increased N 2 O formation in the lean stage. In conclusion, the results of this study will be considered in the context of developing optimized two-stage RQL combustors for ammonia.

Combustion↗