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Datasets for high hydrogen content syngas fuel variability effect on combustion physicochemical properties.

ABSTRACT: The dataset presented in this article is related to the uncertainty quantification of fuel variability effect on high hydrogen content syngas combustion physicochemical properties. The 1D flame data included in this dataset are collected using PREMIX module available in Chemkin-Pro. Inputs to and outputs collected from the PREMIX module are generated and post-processed using UQTk-3.0.4, an open-access uncertainty quantification (UQ) toolkit developed at Sandia National Laboratories. The 1D flame data here refers to the calculation of flame speed, flame temperature, NO emission, etc. using three detailed chemical mechanisms: the GRI-Mech 3.0, the San Diego, and the NUI Galway Mechanism. The main analysis performed using UQTk-3.0.4 focuses on obtaining main and joint sensitivity effects (Sobol Indices) of uniformly distributed fuel uncertainty on 1D premixed physicochemical property. Other parameters such as the resulted probability density function or fluctuation of these properties are also explored. This new and original dataset is suitable for further analyzing fuel variability effect on other significant flame controlling parameters such as Karlovitz number, flame thickness, etc. in the discipline of turbulent combustion simulation.

SUBMITTER: Zhang K

PROVIDER: S-EPMC6992945 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Datasets for high hydrogen content syngas fuel variability effect on combustion physicochemical properties.

Zhang Kai K Jiang Xi X

Data in brief 20200111

The dataset presented in this article is related to the uncertainty quantification of fuel variability effect on high hydrogen content syngas combustion physicochemical properties. The 1D flame data included in this dataset are collected using PREMIX module available in Chemkin-Pro. Inputs to and outputs collected from the PREMIX module are generated and post-processed using UQTk-3.0.4, an open-access uncertainty quantification (UQ) toolkit developed at Sandia National Laboratories. The 1D flame ...[more]

PMID: 32016139

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Project description:The physicochemical properties of combustion particles that promote lung toxicity are not fully understood, hindered by the fact that combustion particles vary based on the fuel and combustion conditions. Real-world combustion-particle properties also continually change as new fuels are implemented, engines age, and engine technologies evolve. This work used laboratory-generated particles produced under controlled combustion conditions in an effort to understand the relationship between different particle properties and the activation of established toxicological outcomes in human lung cells (H441 and THP-1). Particles were generated from controlled combustion of two simple biofuel/diesel surrogates (methyl decanoate and dodecane/biofuel-blended diesel (BD), and butanol and dodecane/alcohol-blended diesel (AD)) and compared to a widely studied reference diesel (RD) particle (NIST SRM2975/RD). BD, AD, and RD particles exhibited differences in size, surface area, extractable chemical mass, and the content of individual polycyclic aromatic hydrocarbons (PAHs). Some of these differences were directly associated with different effects on biological responses. BD particles had the greatest surface area, amount of extractable material, and oxidizing potential. These particles and extracts induced cytochrome P450 1A1 and 1B1 enzyme mRNA in lung cells. AD particles and extracts had the greatest total PAH content and also caused CYP1A1 and 1B1 mRNA induction. The RD extract contained the highest relative concentration of 2-ring PAHs and stimulated the greatest level of interleukin-8 (IL-8) and tumor necrosis factor-alpha (TNF?) cytokine secretion. Finally, AD and RD were more potent activators of TRPA1 than BD, and while neither the TRPA1 antagonist HC-030031 nor the antioxidant N-acetylcysteine (NAC) affected CYP1A1 or 1B1 mRNA induction, both inhibitors reduced IL-8 secretion and mRNA induction. These results highlight that differences in fuel and combustion conditions affect the physicochemical properties of particles, and these differences, in turn, affect commonly studied biological/toxicological responses.

Dataset Information

Datasets for high hydrogen content syngas fuel variability effect on combustion physicochemical properties.

Publications

Datasets for high hydrogen content syngas fuel variability effect on combustion physicochemical properties.

Similar Datasets

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