Measurement of methane autoignition delays in carbon dioxide and argon diluents at high pressure conditions

Karimi, Miad; Ochs, Bradley A.; Liu, Zefang; Ranjan, Devesh; Sun, Wenting

doi:10.1016/j.combustflame.2019.03.020

Cited by 36 publications

(31 citation statements)

References 50 publications

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“…However, due to the fact that the experiments were performed at very high pressure, the discrepancy between the OH and OH * profiles were minimal, and the numerical IDT could therefore be evaluated at the moment of maximum change of OH. This was also confirmed by personal communication with the authors of the paper [51]. The experiments were performed at stoichiometric (φ = 1) and rich (φ = 2) conditions.…”

Section: Test Case 2: Ignition Delay Time At High Pressures Using Data From a Shock-tubesupporting

confidence: 63%

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OptiSMOKE++: A toolbox for optimization of chemical kinetic mechanisms

Fürst

Bertolino

Cuoci

et al. 2021

Computer Physics Communications

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As detailed chemical mechanisms are becoming viable for large scale simulations, knowledge and control of the uncertainty correlated to the kinetic parameters are becoming crucial to ensure accurate numerical predictions. A flexible toolbox for the optimization of chemical kinetics has therefore been developed in this work. The toolbox is able to use different optimization methodologies, as well as it can handle a large amount of uncertain parameters simultaneously. It can also handle experimental targets from different sources: Batch reactors, Plug Flow Reactors, Perfectly Stirred Reactors, Rapid Compression Machines and Laminar Flame Speeds. This work presents the different features of this toolbox together with five different test cases which exemplifies these features.

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Section: Test Case 2: Ignition Delay Time At High Pressures Using Data From a Shock-tubesupporting

confidence: 63%

“…For this test case, the experimental targets consist of IDT of methane diluted in carbon dioxide in a ST, at high pressures (100 bar) [51]. The IDT was experimentally evaluated at the moment where the maximum change of the exited species OH * Fig.…”

Section: Test Case 2: Ignition Delay Time At High Pressures Using Data From a Shock-tubementioning

confidence: 99%

OptiSMOKE++: A toolbox for optimization of chemical kinetic mechanisms

Fürst

Bertolino

Cuoci

et al. 2021

Computer Physics Communications

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show abstract

“…Foundational fuel chemistry model (FFCM-1) [49], AramcoMech 3.0 model [50], and a model from Hashemi et al (H68) [44] are developed based on such experiments. Figure 1 benchmarks the ignition delays as predicted by several models against the experimental data [51]. As observed, GRI 3.0 notably underpredicts the measured data at high pressures, while FFCM-1 best matches the experimental data at 100 bar, and H68 model [44] performs best at 200 bar.…”

Section: Introductionmentioning

confidence: 53%

Skeletal Reaction Model Generation for Atmospheric and High Pressure Combustion of Methane

Liu¹,

Babaee²,

Givi³

et al. 2022

Preprint

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Skeletal reaction models for atmospheric and high pressure combustion of methane are generated from detailed kinetics models through the forced-optimally time dependent (f-OTD) methodology. In the f-OTD method, local sensitivities are decomposed to the multiplication of two low-rank time-dependent matrices.The evolution equation of these matrices are derived from the governing equations of the system. Modeled sensitivities are then analyzed temporally to rank the species based on their importance and produce different skeletal models with different number of species. Skeletal reduction with the f-OTD method is conducted of two detailed kinetics models for methane combustion: the GRI-Mech 3.0 for atmospheric pressure and the FFCM-1 for high pressures. A series of skeletal models with different levels of accuracy are derived in each case. The performances of the generated models are compared against two detailed models (GRI-Mech 3.0 and FFCM-1) based on their ability in predicting ignition delays, laminar flame speeds, and flame extinctions. The effect of pressure on the significance of specific reactions are also analyzed for high pressure combustion.

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“…In addition to the high-resolution discretization schemes, a reliable detailed kinetics mechanism covering high-pressure conditions is another necessary component for the accurate diffusion ignition simulations. Sun’s recent shock tube experiments showed that all the high-pressure experimental trends of high-pressure CH 4 /O 2 /Ar mixture ignition delay are reasonably captured by the Saudi Aramco 2.0 reaction mechanism. − Thus, the submechanism of CH 4 obtained from the Saudi Aramco 2.0 model is employed here, which consists of 312 reactions in 53 species. All the numerical schemes employed in our in-house code are summarized in Table .…”

Section: Methodsmentioning

confidence: 99%

Inhibition Mechanism of CH₄ Addition on the Pressurized Hydrogen Spontaneous Ignition

Zhong

Gou

2021

Energy Fuels

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It is well known that the high spontaneous ignition risk of pressurized hydrogen poses a serious threat to hydrogen storage safety. Aiming to reveal the inhibition mechanism of the fuel-blending strategy on autoignition, the spontaneous ignition of the H 2 /CH 4 mixture suddenly released into a one-dimensional (1D) tube at high pressure is studied numerically with highresolution difference schemes and a detailed kinetics model. First, the basic spontaneous ignition features are obtained. It is observed that under the shock wave compression effect, the air in front of the high-pressure hydrogen jet is heated up to 1200 K when the bursting pressure is 90 atm. Thus, the onset of autoignition always occurs under a quite fuel-lean, high-pressure, and hightemperature condition. Moreover, after autoignition, multiflame regions are found in the mixing layer, which are two short-lived premixed flames and a diffusion flame. The 1D result suggests that the occurrence of the spontaneous ignition is not dependent on the wall boundary layer and the shock wave interactions. Subsequently, autoignition under different blending levels is examined. The comparison shows that a minor amount of CH 4 addition (3% by mole) results in a sixfold increase in the ignition delay. Through the simulations of the fuel with artificial property, reaction sensitivity analysis, and Damkoḧler number evaluation, it was found that the addition decreases the shocked air temperature, reduces the H radical accumulation rate, and increases the relative loss of free radicals on the reaction front. Our work demonstrates that the key to the fuel-blending strategy for diffusion autoignition inhibition is increasing the fuel molecular weight.

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Measurement of methane autoignition delays in carbon dioxide and argon diluents at high pressure conditions

Cited by 36 publications

References 50 publications

OptiSMOKE++: A toolbox for optimization of chemical kinetic mechanisms

OptiSMOKE++: A toolbox for optimization of chemical kinetic mechanisms

Skeletal Reaction Model Generation for Atmospheric and High Pressure Combustion of Methane

Inhibition Mechanism of CH₄ Addition on the Pressurized Hydrogen Spontaneous Ignition

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Measurement of methane autoignition delays in carbon dioxide and argon diluents at high pressure conditions

Cited by 36 publications

References 50 publications

OptiSMOKE++: A toolbox for optimization of chemical kinetic mechanisms

OptiSMOKE++: A toolbox for optimization of chemical kinetic mechanisms

Skeletal Reaction Model Generation for Atmospheric and High Pressure Combustion of Methane

Inhibition Mechanism of CH4 Addition on the Pressurized Hydrogen Spontaneous Ignition

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Product

Resources

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Inhibition Mechanism of CH₄ Addition on the Pressurized Hydrogen Spontaneous Ignition