WeChat Mini Program
Old Version Features

Estimation and Testing of Single-Step Oxidation Reactions for Hydrogen and Methane in Low-Oxygen, Elevated Pressure Conditions

FUEL(2024)

Univ Adelaide

Cited 0|Views11
Abstract
Advanced combustion concepts, such as moderate or intense low-oxygen dilution (MILD) combustion, offer a reduction in NOx emissions and increased thermal efficiency. MILD is characterised by low-oxygen, high-temperature conditions, where finite-rate chemistry effects are significant. Modelling this regime using reduced or single-step chemistry remains a challenge in part due to the finite-rate chemistry. This work proposes a generalised method for assigning Arrhenius coefficients of a single-step reaction using the outputs of a detailed mechanism. Assigning the typical chemical conservation equation to a progress variable, activation energy and pre-exponential factor for an Arrhenius kinetics global reaction are determined for hydrogen and methane across a number of conditions, with the proposed method extended to n-heptane as well. The temperature exponent in the modified Arrhenius equation is determined by minimising the ignition delay error between detailed and single-step simulations. Functional forms of each coefficient are calculated from a multivariate regression, dependent on initial temperature, pressure, and oxidant mole fraction. The predicted mechanisms are compared against the detailed kinetics in closed homogeneous batch reactors, with comparisons for hydrogen extended to both laminar opposed flow diffusion flames, and computational fluid dynamics (CFD) simulations. Ignition delay and equilibrium temperature are both well predicted for all three fuels in the batch reactors. Notably, the negative temperature coefficient behaviour of n-heptane is successfully recreated with the single-step mechanism. Temperature and heat release of hydrogen flames are well captured in both opposed flow laminar flames, and in turbulent CFD simulations. The computational time was also significantly reduced through the single-step mechanisms, resulting in ∼100 times reduction in compute time for CFD simulations. The function form of the Arrhenius coefficients shows promise for extension outside of the ranges and fuels analysed herein, and presents interesting phenomena for exploring how initial reactant temperature and pressure influence the effective activation energy of an oxidation process.
More
Translated text
Key words
Autoignition,Mild combustion,Combustion theory,Hydrogen combustion,Pressurised combustion
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined