Hydrocarbon combustion reaction models from both ends--the foundational fuels and JP10
Abstract/Contents
- Abstract
- Due to the hierarchical nature of high-temperature hydrocarbon oxidation, modeling the combustion chemistry of higher hydrocarbon fuels typically requires a fuel-specific reaction model that describes the fragmentation of the fuel to small species, and a foundational fuel chemistry model that describes the oxidation of these species. Shared by the combustion of large hydrocarbons, the foundational fuel chemistry is also the rate-limiting step and therefore a crucial part for constructing reliable combustion models for any higher hydrocarbons. The dissertation studies the aforementioned problems from both ends. A detailed reaction kinetic model of the foundational fuel combustion is comprised of elementary chemical reactions and their associated rate coefficients. Each of the rate coefficients comes with some uncertainty. The inherent uncertainties of the rate parameters propagate into model predictions and need to be properly quantified. Without characterizing the uncertainty, a reaction model merely represents a feasible combination of rate parameters within a high-dimensional uncertainty space. The Foundational Fuel Chemistry Model (FFCM) is an effort directed at developing a reliable combustion model for the foundational fuels with rate parameters optimized and uncertainty minimized. The first version, FFCM-1, optimized for H2, H2/CO, CH2O and CH4 combustion was constrained with carefully evaluated fundamental combustion data that includes laminar flame speeds, shock tube ignition delay times, shock tube species profiles, and flow reactor species profiles. It has been shown that the model reconciles all the experimental targets chosen and has significantly reduced prediction uncertainties. The remaining kinetic uncertainties in FFCM-1 were further analyzed with extinction and ignition residence time predictions in perfectly-stirred reactor conditions. The reactions that were responsible for the remaining prediction uncertainties were studied with an impact factor analysis over a wide range of temperature, pressure and equivalence ratio. The optimization and uncertainty quantification procedure was then extended to also include temperature dependency by considering the joint optimization of pre-exponential factors and activation energies. An effective temperature was defined for every target and utilized in the response surface derivation. The resulting temperature-dependent uncertainties of key reactions in H2/CO flames in a test problem were discussed. JP10 was studied as a single-component large-fuel example, using the Hybrid Chemistry (HyChem) approach. The HyChem approach assumes a decoupled fuel pyrolysis and oxidation of pyrolysis products. The pyrolysis model is described with highly-lumped steps and optimized against experimental data from shock tube and flow reactor species profiles and shock tube ignition delay. Special attention was paid to the unique molecular structure of the fuel in the lumped pyrolysis reactions, and the overall performance of the model is shown to be satisfactory.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Tao, Yujie |
|---|---|
| Degree supervisor | Wang, Hai, 1962- |
| Thesis advisor | Wang, Hai, 1962- |
| Thesis advisor | Bowman, Craig T. (Craig Thomas), 1939- |
| Thesis advisor | Hanson, Ronald |
| Degree committee member | Bowman, Craig T. (Craig Thomas), 1939- |
| Degree committee member | Hanson, Ronald |
| Associated with | Stanford University, Department of Mechanical Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Yujie Tao. |
|---|---|
| Note | Submitted to the Department of Mechanical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Yujie Tao
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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